(upbeat music) >> Okay, welcome back everyone. I'm John Furrier here in theCUBE, in Palo Alto for "CUBE Conversation" with Chris Jones, Director of Product Management at Platform9. I've got a series of questions, had a great conversation earlier. Chris, I have a couple questions for you, what do you think? >> Let's do it, John. >> Okay, how does Platform9 Solution, you- can it be used on any infrastructure anywhere, cloud, edge, on-premise? >> It can, that's the beauty of our control plane, right? It was born in the cloud, and we primarily deliver that SaaS, which allows it to work in your data center, on bare metal, on VMs, or with public cloud infrastructure. We now give you the ability to take that control plane, install it in your data center, and then use it with anything, or even in air gap. And that includes capabilities with bare metal orchestration as well. >> Second question. How does Platform9 ensure maximum uptime, and proactive issue resolution? >> Oh, that's a good question. So if you come to Platform nine we're going to talk about always on assurance. What is driving that is a system of three components around self-healing, monitoring, and proactive assistance. So our software will heal broken things on nodes, right? If something stops running that should be running, it will attempt to restart that. We also have monitoring that's deployed with everything. So you build a cluster in AWS, well, we put open source monitoring agents, that are actually Prometheus, on every single node. That means it's resilient, right? So if you lose a node, you don't lose monitoring. But that data importantly comes back to our control plane, and that's the control plane that you can put in your data center as well. That data is what alerts us, and you as a user, anytime of the day that something's going wrong. Let's say etcd latency, good example, etcd is going slow. We'll find out, we might not be able to take restorative action immediately, but we're definitely going to reach out and say,, "You have a problem, let's get ahead of this and let's prevent that from becoming a bigger problem." And that's what we're delivering. When we say always on assurance, we're talking about self-healing, we're talking about remote monitoring, we're talking about being proactive with our customers, not waiting for the phone call or the support desk ticket saying, "Oh we think something's not working." Or worse, the customer has an outage. >> Awesome. Thanks for sharing. Can you explain the process for implementing Platform9 within a company's existing infrastructure. >> Are we doing air gap, or on-prem or SaaS approached? SaaS approach I think is by far the easiest, right? We can build a dedicated Platform9 control plane instance in a manner of minutes, for any customer. So when we do a proof of concept or onboarding, we just literally put in an email address, put in the name you want for your fully qualified domain name, and your instance is up. From that point onwards, the user can just log in, and using our CLI, talk to any number of, say, virtual machines, or physical servers in their environment for, you know, doing this in a data center or colo, and say, "I want these to be my Kubernetes control plane nodes. Here's the five of them. Here's the VIP for the load balancing, the API server and here are all of my compute nodes." And that CLI will work with the SaaS control plane, and go and build the cluster. That's as simple as it, CentOS, Ubuntu, just plain old operating system. Our software takes care of all the prerequisites, installing all the pieces, putting down MetalLB, CoreDNS, Metrics Server, Kubernetes dashboard, etcd backups. You built some servers. That's essentially what you've done, and the rest is being handled by Platform9. It's as simple as that. >> Great, thanks for that. What are the two traditional paths for companies considering the cloud native journey? The two paths. >> The traditional paths. I think that's your engineering team running so fast that before you even realize that you've got, you know, 10 EKS clusters. Or, hey, we can do this. You know, I've got the I can build it mentality. Let's go DIY completely open source Kubernetes on our infrastructure, and we're going to piecemeal build it all up together. They're, I think the pathways that people traditionally look at this journey, as opposed to having that third alternative saying can I just consume it on my infrastructure, be it cloud or on-premise or at the edge. >> Third is the new way, you guys do that. >> That's been our focus since the company was, you know, brought together back in the open OpenStack days. >> Awesome, what's the makeup of your customer base? Is there a certain pattern to the size or environments that you guys work with? Is there a pattern or consistency to your customer base? >> It's a spread, right? We've got large enterprises like Juniper, and we go all the way down to people with 20, 30, 50 nodes in total. We've got people in banking and finance, we've got things all the way through to telecommunications and storage infrastructure. >> What's your favorite feature of Platform9? >> My favorite feature? You know, if I ask, should I say this as a pre-sales engineer, let me show you a favorite thing. My immediate response is, I should never do this. (John laughs) To me it's just being able to define my cluster and say, go. And in five minutes I have that environment, I can see everything that's running, right? It's all unified, it's one spot, right? I'm a cluster admin. I said I wanted three control plane, 25 workers. Here's the infrastructure, it creates it, and once it's built, I can see everything that's running, right? All the applications that are there. One UI, I don't have to go click around. I'm not trying to solve things or download things. It's the fact that it's unified and just delivered in one hit. >> What is the one thing that people should know about Platform9 that they might not know about it? >> I think it's that we help developers and engineers as much as we can help our operations teams. I think, for a long time we've sort of targeted that user and said, hey, we, we really help you. It's like, but why are they doing this? Why are they building any infrastructure or any cloud platform? Well, it's to run applications and services, to help their customers, but how do they get there? There's people building and writing those things, and we're helping them, right? For the last two years, we've been really focused on making it simple, and I think that's an important thing to know. >> Chris, thanks so much, appreciate it. >> Yeah, thank you, John. >> Okay, that's theCUBE Q&A session here with Platform9. I'm John Furrier, thanks for watching. (light music)

>> TheCUBE presents Ignite 22 brought to you by Palo Alto Networks. >> Welcome back to Las Vegas, everyone. We're glad you're with us. This is theCUBE live at Palo Alto Ignite 22 at the MGM Grant in Las Vegas. Lisa Martin here with Dave Vellante, day one of our coverage. We've had great conversations. The cybersecurity landscape is so interesting Dave, it's such a challenging problem to solve but it's so diverse and dynamic at the same time. >> You know, Lisa theCUBE started in May of 2010 in Boston. We called it the chowder event, chowder and Lobster. It was a EMC world, 2010. BJ Jenkins, who's here, of course, was a longtime friend of theCUBE and made the, made the transition into from, well, it's still data, data to, to cyber. So >> True. And BJ is back with us. BJ Jenkins, president Palo Alto Networks great to have you back on theCUBE. >> It is great to be here in person on theCube >> Isn't it great? >> In Vegas. It's awesome. >> And we can tell by your voice will be, will be gentle. You, you've been in Vegas typical Vegas occupational hazard of losing the voice. >> Yeah. It was one of the benefits of Covid. I didn't lose my voice at home sitting talking to a TV. You lose it when you come to Vegas. >> Exactly. >> But it's a small price to pay. >> So things kick off yesterday with the partner summit. You had a keynote then, you had a customer, a CISO on stage. You had a keynote today, which we didn't get to see. But talk to us a little bit about the lay of the land. What are you hearing from CISOs, from CIOs as we know security is a board level conversation. >> Yeah, I, you know it's been an interesting three or four months here. Let me start with that. I think, cybersecurity in general is still front and center on CIOs and CISO's minds. It has to be, if you saw Wendy's presentation today and the threats out there companies have to have it front and center. I do think it's been interesting though with the macro uncertainty. We've taken to calling this year the revenge of the CFO and you know these deals in cybersecurity are still a top priority but they're getting finance and procurements, scrutiny which I think in this environment is a necessity but it's still a, you know, number one number two imperative no matter who you talked to, in my mind >> It was interesting what Nikesh was saying in the last conference call that, hey we just have to get more approvals. We know this. We're, we're bringing more go-to-market people on board. We, we have, we're filling the pipeline 'cause we know they're going to split up deals big deals go into smaller chunks. So the question I have for you is is how are you able to successfully integrate those people so that you can get ahead of that sort of macro transition? >> Yeah I, you know, I think there's two things I'd say about uncertain macro situations and Dave, you know how old I am. I'm pretty old. I've been through a lot of cycles. And in those cycles I've always found stronger companies with stronger value proposition separate themselves actually in uncertain, economic times. And so I think there's actually an opportunity here. The message tilts a little bit though where it's been about innovation and new threat vectors to one of you have 20, 30, 40 vendors you can consolidate become more effective in your security posture and save money on your TCOs. So one of the things as we bring people on board it's training them on that business value proposition. How do you take a customer who's got 20 or 30 tools take 'em down to 5 or 10 where Palo is more central and strategic and be able to demonstrate that value. So we do that through, we're making a huge investment in our people but macroeconomic times also puts some stronger people back on the market and we're able to incorporate them into the business. >> What are the conditions that are necessary for that consolidation? Like I would imagine if you're, if you're a big customer of a big, you know, competitor of yours that that migration is going to be harder than if you're dealing with lots of little point tools. Do those, do those point tools, are they sort of is it the end of the subscription? Is it just stuff that's off the books now? What's, the condition that is ripe for that kind of consolidation? >> Look, I think the challenge coming into this year was skills. And so customers had all of these point products. It required a lot more human intervention as Nikesh was talking about to integrate them or make them work. And as all of us know finding people with cybersecurity skills over the last 12 months has been incredibly hard. That drove, if you know, if you think about that a CIO and a CISO sitting there going, I have all all this investment in tools. I don't have the people to operate 'em. What do I need to do? What we tried to do is elevate that conversation because in a customer, everybody who's bought one of those, they they bought it to solve a problem. And there's people with affinity for that tool. They're not just going to say I want to get consolidated and give up my tool. They're going to wrap their arms around it. And so what we needed to do and this changed our ecosystem strategy too how we leverage partners. We needed to get into the CIO and CISO and say look at this chaos you have here and the challenges around people that it's, it's presenting you. We can help solve that by, by standardizing, consolidating taking that integration away from you as Nikesh talked about, and making it easier for your your high skill people to work on high skill, you know high challenges in there. >> Let chaos reign, and then reign in the chaos. >> Yes. >> Andy Grove. >> I was looking at some stats that there's 26 million developers but less than 3 million cybersecurity professionals. >> Talked about that skills gap and what CISOs and CIOs are facing is do you consider from a value prop perspective Palo Alto Networks to be a, a facilitator of helping organizations deal with that skills gap? >> I think there's a short term and a long term. I think Nikesh today talked about the long term that we'll never win this battle with human beings. We're going to have to win it with automation. That, that's the long term the short term right here and now is that people need people with cybersecurity skills. Now what we're trying to do, you know, is multifaceted. We work with universities to standardize programs to develop skills that people can come into the marketplace with. We run our own programs inside the company. We have a cloud academy program now where we take people high aptitude for sales and technical aptitude and we will put them through a six month boot camp on cloud and they'll come out of that ready to really work with the leading experts in cloud security. The third angle is partners, right, there are partners in the marketplace who want to drive their business into high services areas. They have people, they know how to train. We give them, we partner with them to give them training. Hopefully that helps solve some of the short-term gaps that are out there today. >> So you made the jump from data storage to security and >> Yeah. >> You know, network security, all kinds of security. What was that like? What you must have learned a lot in the last better part of a decade? >> Yeah. >> Take us through that. >> You know, so the first jump was from EMC. I was 15 years there to be CEO of Barracuda. And you know, it was interesting because EMC was, you know large enterprise for the most part. At Barracuda we had, you know 250,000 small and mid-size enterprises. And it was, it's interesting to get into security in small and mid-size businesses because, you know Wendy today was talking about nation states. For small and mid-size business, it's common thievery right? It's ransomware, it's, and, those customers don't have, you know, the human and financial resources to keep up with the threat factor. So, you know, Nikesh talked about how it's taken 'em four and a half years to get into cybersecurity. I remember my first week at Barracuda, I was talking with a customer who had, you know, breached data shut down. There wasn't much bitcoin back then so it was just a pure ransom. And I'm like, wow, this is, you know, incredible industry. So it's been a good, you know, transition for me. I still think data is at the heart of all of this. Right? And I have always believed there's a strong connection between the things I learned growing up at EMC and what I put into practice today at Palo Alto Networks. >> And how about a culture because I, you know I know have observed the EMC culture >> Yeah. >> And you were there in really the heyday. >> Yeah. >> Right? Which was an awesome place. And it seems like Palo Alto obviously, different times but you know, similar like laser focus on solving problems, you know, obviously great, you know value sellers, you know, you guys aren't the commodity >> Yeah. For Product. But there seemed to be some similarities from afar. I don't know Palo Alto as well as I know EMC. >> I think there's a lot. When I joined EMC, it was about, it was 2 billion in in revenue and I think when I left it was over 20, 20, 21. And, you know, we're at, you know hopefully 5, 5 5 in revenue. I feel like it's this very similar, there's a sense of urgency, there's an incredible focus on the customer. you know, Near and Moche are definitely different individuals but the both same kind of disruptive, Israeli force out there driving the business. There are a lot of similarities. I, you know, the passion, I feel privileged as a, you know go to market person that I have this incredible portfolio to go, you know, work with customers on. It's a lucky position to be in, but very I feel like it is a movie I've seen before. >> Yeah. And but, and the course, the challenges from the, the target that you're disrupting is different. It was, you know, EMC had a lot of big, you know IBM obviously was, you know, bigger target whereas you got thousands of, you know, smaller companies. >> Yes. >> And, and so that's a different dynamic but that's why the consolidation play is so important. >> Look at, that's why I joined Palo Alto Networks when I was at Barracuda for nine years. It just fascinated me, that there was 3000 plus players in security and why didn't security evolve like the storage market did or the server market or network where working >> Yeah, right. >> You know, two or three big gorillas came to, to dominate those markets. And it's, I think it's what Nikesh talked about today. There was a new problem in best of breed. It was always best of breed. You can never in security go in and, you know, say, Hey it's good I saved us some money but I got the third best product in the marketplace. And there was that kind of gap between products. I, believe in why I joined here I think this is my last gig is we have a chance to change that. And this is the first company as I look from the outside in that had best of breed as, you know Nikesh said 13 categories. >> Yeah. >> And you know, we're in the leaders quadrant and it's a conversation I have with customers. You don't have to sacrifice best of breed but get the benefits of a platform. And I, think that resonates today. I think we have a chance to change the industry from that viewpoint. >> Give us a little view of the voice of the customer. You had, was it Sabre? >> Yeah. >> That was on >> Scott Moser, The CISO from Sabre. >> Give us a view, what are you hearing from the voice of the customer? Obviously they're quite a successful customer but challenges, concerns, the partnership. >> Yeah. Look, I think security is similar to industries where we come up with magic marketing phrases and, you know, things to you know, make you want to procure our solutions. You know, zero trust is one. And you know, you'll talk to customers and they're like, okay, yes. And you know, the government, right? Joe, Joe Biden's putting out zero trust executive orders. And the, the problem is if you talk to customers, it's a journey. They have legacy infrastructure they have business drivers that you know they just don't deal with us. They've got to deal with the business side who's trying to make the money that keeps the, the company going. it's really helped them draw a map from where they're at today to zero trust or to a better security architecture. Or, you know, they're moving their apps into the cloud. How am I going to migrate? Right? Again, that discussion three years ago was around lift and shift, right? Today it's about, well, no I need cloud native developed apps to service the business the way I want to, I want to service it. How do I, so I, I think there's this element of a trusted partner and relationship. And again, I think this is why you can't have 40 or 50 of those. You got to start narrowing it down if you want to be able to meet and beat the threats that are out there for you. So I, you know, the customers, I see a lot of 'em. It's, here's where I'm at help me get here to a better position. And they know it's, you know Scott said in our keynote today, you don't just, you know have layer three firewall policies and decide, okay tomorrow I'm going to go to layer seven. That, that's not how it works. Right? There's, and, and by the way these things are a mission critical type areas. So there's got to be a game plan that you help customers go through to get there. >> Definitely. Last question, my last question for you is, is security being a board level conversation I was reading some stats from a survey I think it was the what's new in Cypress survey that that Palo Alto released today that showed that while significant numbers of organizations think they've got a cyber resiliency playbook, there's a lot of disconnect or lack of alignment at the boardroom. Are you in those conversations? How can you help facilitate that alignment between the executive team and the board when it comes to security being so foundational to any business? >> Yeah, it's, I've been on three, four public company boards. I'm on, I'm on two today. I would say four years ago, this was a almost a taboo topic. It was a, put your head in the sand and pray to God nothing happened. And you know, the world has changed significantly. And because of the number of breaches the impact it's had on brand, boards have to think about this in duty of care and their fiduciary duty. Okay. So then you start with a board that may not have the technical skills. The first problem the security industry had is how do I explain your risk profile in a way you can understand it. I'm, I'm on the board of Generac that makes home generators. It's a manufacturing, you know, company but they put Wifi modules in their boxes so that the dealers could help do the maintenance on 'em. And all of a sudden these things were getting attacked. Right? And they're being used for bot attacks. >> Yeah. >> Everybody on their board had a manufacturing background. >> Ah. >> So how do you help that board understand the risk they have that's what's changed over the last four years. It's a constant discussion. It's one I have with CISOs where they're like help us put it in layman's terms so they understand they know what we're doing and they feel confident but at the same time understand the marketplace better. And that's a journey for us. >> That Generac example is a great one because, you know, think about IOT Technologies. They've historically been air gaped >> Yes. >> By design. And all of a sudden the business comes in and says, "Hey we can put wifi in there", you know >> Connect it to a home Wifi system that >> Make our lives so much easier. Next thing you know, it's being used to attack. >> Yeah. >> So that's why, as you go around the world are you discerning, I know you were just in Japan are you discerning significant differences in sort of attitudes toward, towards cyber? Whether it's public policy, you know things like regulation where you, they don't want you sharing data, but as as a cyber company, you want to share that data with you know, public and private? >> Look it, I, I think around the world we see incredible government activity first of all. And I think given the position we're in we get to have some unique conversations there. I would say worldwide security is an imperative. I, no matter where I go, you know it's in front of everybody's mind. The, on the, the governance side, it's really what do we need to adapt to make sure we meet local regulations. And I, and I would just tell you Dave there's ways when you do that, and we talk with governments that because of how they want to do it reduce our ability to give them full insight into all the threats and how we can help them. And I do think over time governments understand that we can anonymize the data. There's, but that, that's a work in process. Definitely there is a balance. We need to have privacy, we need to have, you know personal security for people. But there's ways to collect that data in an anonymous way and give better security insight back into the architectures that are out there. >> All right. A little shift the gears here. A little sports question. We've had some great Boston's sports guests on theCUBE right? I mean, Randy Seidel, we were talking about him. Peter McKay, Snyk, I guess he's a competitor now but you know, there's no question got >> He got a little funding today. I saw that. >> Down round. But they still got a lot of money. Not of a down round, but they were, but yeah, but actually, you know, he was on several years ago and it was around the time they were talking about trading Brady. He said Never trade Brady. And he got that right. We, I think we can agree Brady's the goat. >> Yes. >> The big question I have for you is, Belichick. Do you ever question Has your belief in him as the greatest coach of all time wavered, you know, now that- No. Okay. >> Never. >> Weigh in on that. >> Never, he says >> Still the Goat. >> I'll give you my best. You know, never In Bill we trust. >> Okay. Still. >> All right >> I, you know, the NFL is a unique property that's designed for parody and is designed, I mean actively designed to not let Mr. Craft and Bill Belichick do what they do every year. I feel privileged as a Boston sports fan that in our worst years we're in the seventh playoff spot. And I have a lot of family in Chicago who would kill for that position, by the way. And you know, they're in perpetual rebuilding. And so look, and I think he, you know the way he's been able to manage the cap and the skill levels, I think we have a top five defense. There's different ways to win titles. And if I, you know, remember in Brady's last title with Boston, the defense won us that Super Bowl. >> Well thanks for weighing in on that because there's a lot of crazy talk going on. Like, 'Hey, if he doesn't beat Arizona, he's got to go.' I'm like, what? So, okay, I'm sometimes it takes a good good loyal fan who's maybe, you know, has >> The good news in Boston is we're emotional fans too so I understand you got to keep the long term long term in mind. And we're, we're in a privileged position in Boston. We've got Celtics, we've got Bruins we've got the Patriots right on the edge of the playoffs and we need the Red Sox to get to work. >> Yeah, no, you know they were last, last year so maybe they're going to win it all like they usually do. So >> Fingers crossed. >> Crazy worst to first. >> Exactly. Well you said, in Bill we trust it sounds like from our conversation in BJ we trust from the customers, the partners. >> I hope so. >> Thank you so much BJ, for coming back on theCUBE giving us the lay of the land, what's new, the voice of the customer and how Palo Alto was really differentiated in the market. We always appreciate your, coming on the show you >> Honor and privilege seeing you here. Thanks. >> You may be thinking that you were watching ESPN just now but you know, we call ourselves the ESPN at Tech News. This is Lisa Martin for Dave Vellante and our guest. You're watching theCUBE, the Leader and live emerging in enterprise tech coverage. (upbeat music)

>>Hello, wonderful humans and welcome back to The Cube's Thrilling live coverage of AWS Reinvent here in Las Vegas, Nevada. I'm joined by my fantastic co-host, John Farer. John, things are really ramping up in here. Day one. >>Yep, it's packed already. I heard 70,000 maybe attendees really this year. I just saw that on Twitter. Again, it continues to show that over the past 10 years we've been here, you're seeing some of the players that were here from the beginning growing up and getting bigger and stronger, becoming more platforms, not just point solutions. You're seeing new entrants coming in, new startups, and the innovation you start to see happening, it's really compelling to fun to watch. And our next segment, we have multi 10 time Cube alumni coming on and a first timer, so it should be great. We'll get into some of the innovation, >>Not only as this guest went on the cube 10 times, he also spoke at the first AWS reinvent, just like you were covering it here with Cube. But without further ado, please welcome Ronan and Kevin from NetApp. Thank you gentlemen, both for being here and for matching in your dark blue. How's the show going for you? Ronan, I'm gonna ask you first, you've been here since the beginning. How does it feel in 2022? >>First, it's amazing to see so many people, right? So many humans in one place, flesh and blood. And it's also amazing to see, it's such a celebration for people in the cloud, right? Like this is our, this is our event, the people in the cloud. I'm really, really happy to be here and be in the cube as well. >>Fantastic. It, it is a party, it's a cloud party. Yes. How are you feeling being here, Kevin? I'm >>Feeling great. I mean, going all the way back to the early days of Spot T, which was the start that eventually got acquired as Spot by NetApp. I mean this was, this was our big event. This is what we lived for. We've gone, I've gone from everything, one of the smaller booths out here on the floor all the way up to the, the huge booth that we have today. So we've kind of grown along with the AWS ecosystem and it's just a lot of fun to get here, see all the customers and talk to everybody. >>That's a lot of fun. Fun. That's the theme that we've been talking about. And we wrote a story about on, on Silicon Angle, more that growth from that getting in and getting bigger, not just an ISV or part of the startup showcase or ecosystem. The progression of the investment on how cloud has changed deliverables. You've been part of that wave. What's the biggest walk away, what's, and what's the most important thing going on now cuz it's not stopping. You got new interests coming in and the folks are rising with the tide and getting platforms built around their products. >>Yeah, I would say, you know, years ago is, is cloud in my decision path and now it's cloud is in my decision path. How much is it and how am I going to use it? And I think especially coming up over the next year, macroeconomic events and everything going on is how do I make my next dollar in the cloud go further than my last dollar? Because I know I'm gonna be there, I know I'm gonna be growing in the cloud, so how do I effectively use it to run my business going forward? >>All right, take a minute to explain Spot now part of NetApp. What's the story? What take us through for the folks that aren't familiar with the journey, where it's come from, where it's today? >>Sure. So SPOT is all about cloud optimization. We help all of our customers deploy scale and optimize their applications in the cloud. And what we do is everything from VMs to containers to any type of custom application you want to deploy, we analyze those applications, we find the best price point to run them, we right size them, we do the automation so your DevOps team doesn't have to do it. And we basically make the whole cloud serverless for you at the end of the day. So whatever you're doing in the cloud, we'll manage that for you from the lowest level of the stack all the way up to the highest level financials. >>Is this what you call the evolved cloud state? >>It is in the evolve clouds a little bit more, and Ronan can touch on that a little bit too. The Evolve clouds not only the public cloud but also the cloud that you're building OnPrem, right? A lot of big companies, it's not necessarily a hundred percent one way or the other. The Evolve cloud is which cloud am I on? Am I on an OnPrem cloud and a public cloud or am I on multiple public clouds in an OnPrem cloud? And I think Ronan, you probably have an opinion on that too. >>Yeah, and and I think what we are hearing from our customers is that many of them are in a situation where a lot of their data has been built for years on premises. They're accelerating their move to the cloud, some of them are accelerating, they're moving into multiple cloud and that situation of an on-prem that is becoming cloudy and cloudy all the time. And then accelerated cloud adoption. This is what the customers are calling the Evolve cloud and that's what we're trying to support them in that journey. >>How many customers are you supporting in this Evolve cloud? You made it seem like you can just turnkey this for everyone, which I am here >>For it. Yeah, just to be clear, I mean we have thousands of customers, right? Everything from your small startups, people just getting going with a few VMs all the way to people scaling to tens and thousands of VMs in the cloud or even beyond VM services and you know, tens of millions of spend a month. You know, people are putting a lot of investment into the cloud and we have all walks of life under our, you know, customer portfolio. >>You know, multi-cloud has been a big topic in the industry. We call it super cloud. Cause we think super cloud kind of more represents the destination to multi-cloud. I mean everyone has multiple clouds, but they're best of breed defaults. They're not by design in most cases, but we're starting to see traction towards that potential common level services fix to late. See, I still think we're on the performance game now, so I have to ask, ask you guys. Performance has becoming back in VO speeds and feeds back during the data center days. Well, I wouldn't wanna talk speeds and feeds of solutions and then cloud comes in. Now we're at the era of cloud where people are moving their workloads there. There's a lot more automation going on, A lot more, as you said, part of the decision. It is the path. Yeah. So they say, now I wanna run my workloads on the better, faster infrastructure. No developer wants to run their apps on the slower hardware. >>I think that's a tall up for you. Ronan go. >>I mean, I put out my story, no developer ever said, give me the slower software performance and and pay more fast, >>Fastest find too fastest. >>Speed feeds your back, >>Right? And and performance comes in different, in different parameters, right? They think it is come throughput, it comes through latency. And I think even a stronger word today is price performance, right? How much am I paying for the performance that that I need? NetApp is actually offering a very, very big advantage for customers on both the high end performance as well as in the dollar per performance. That is, that is needed. This is actually one of the key differentiator that Fsx for NetApp on top is an AWS storage based on the NetApp on top storage operating system. This is one of the biggest advantages it is offering. It is SAP certified, for example, where latency is the key, is the key item. It is offering new and fastest throughput available, but also leveraging some advanced features like tiering and so on, is offering unique competitive advantage in the dollar for performance specifically. >>And why, why is performance important now, in your opinion? Obviously besides the obvious of no one wants to run their stuff on the slower infrastructure, but why are some people so into it now? >>I think performance as a single parameter is, is definitely a key influencer of the user experience. None, none of us will, will compromise our our experience. The second part is performance is critical when scale is happening, right? And especially with the scale of data performance to handle massive amounts of data is is becoming more and more critical. The last thing that I'll emphasize is again is the dollar for performance. The more data you have, the more you need to handle, the more critical for you is to handle it in a cost effective way. This is kind of, that's kind of in the, in the, in the secret sauce of the success of every workload. >>There isn't a company or person here who's not thinking about doing more faster for cheaper. So you're certainly got your finger on the pulse With that, I wanna talk about a, a customer case study. A little birdie told me that a major US airline recently just had a mass of when we're where according to my notes response time and customer experience was improved by 17 x. Now that's the type of thing that cuts cost big time. Can one of you tell me a little bit more about that? >>Yeah, so I think we all flew here somehow, right? >>Exactly. It's airlines matter. Probably most folks listening, they're >>Doing very well right now. Yes, the >>Airlines and I think we all also needed to deal with changes in the flights with, with really enormous amount of complexity in managing a business like that. We actually rank and choose what, what airline to use among other things based on the level of service that they give us. And especially at the time of crunch, a lot of users are looking through a lot of data to try to optimize, >>Plus all of them who just work this holiday weekend sidebar >>E Exactly right. Can't even, and Thanksgiving is one of these crunch times that are in the middle of this. So 70 x improvement in performance means a loss seven >>Zero or >>17 1 7 1 7 x Right? >>Well, and especially when we're talking about it looks like 50,000, 50,000 messages per minute that this customer was processing. Yes. That that's a lot. That's almost a thousand messages a second. Wow. I think my math tees up there. Yeah. >>It does allow them to operate in the next level of scale and really increase their support for the customer. It also allows them to be more efficient when it comes to cost. Now they need less infrastructure to give better service across the board. The nice thing is that it didn't require them for a lot of work. Sometimes when the customers are doing their journey to the cloud, one of the things that kind of hold them back is like, is either the fear or, or maybe is the, the concern of how much effort will it take me to achieve the same performance or even a better performance in the cloud? They are a live example that not only can you achieve, you can actually exceed the performance that I have on premises and really give customer a better service >>Customer a better service. And reliability is extremely important there. 99.9%. 99% >>99. Yes. >>Yes. That second nine obviously being very important, especially when we're talking about the order of magnitude of, of data and, and actions being taken place. How much of a priority is, is reliability and security for y'all as a team? >>So reliability is a key item for, for everybody, especially in crunch times. But reliability goes beyond the nines. Specifically reliability goes into how simple it is for you to enable backup n dr, how protected are you against ransomware? This is where netup and, and including the fsx for NETUP on top richness of data management makes a huge difference. If you are able to make your copy undeletable, that is actually a game changer when it comes to, to data protection. And this is, this is something that in the past requires a lot of work, opening vaults and other things. Yeah. Now it becomes a very simple configuration that is attached to every net up on top storage, no matter where it is. >>We heard some news at VMware explorer this past fall. Early fall. You guys were there. We saw the Broadcom acquisition. Looks like it's gonna get finalized maybe sooner than later. Lot of, so a lot of speculation around VMware. Someone called the VMware like where is VMware as in where they now, nice pun it was, it was actually Nutanix people, they go at each other all the time. But Broadcom's gonna keep vse and that's where the bread and butter, that's the, that's the goose that lays the Golden eggs. Customers are there. How do you guys see your piece there with VMware cloud on AWS that integrates solution? You guys have a big part of that ecosystem. We've covered it for years. I mean we've been to every VM world now called explorer. You guys have a huge customer base with VMware customers. What's the, what's the outlook? >>Yeah, and, and I think the important part is that a big part of the enterprise workloads are running on VMware and they will continue to run on VMware in, in, in the future. And most of them will try to run in a hybrid mode if not moving completely to the cloud. The cloud give them unparallel scale, it give them DR and backup opportunities. It does a lot of goodness to that. The partnership that NetApp brings with both VMware as well ass as well as other cloud vendors is actually a game changer. Because the minute that you go to the cloud, things like DR and backup have a different economics connected to them. Suddenly you can do compute less dr definitely on backup you can actually achieve massive savings. NetApp is the only data store that is certified to run with VMware cloud. And that actually opens to the customer's huge opportunity for unparalleled data protection as well as real, real savings, hard savings. And customers that look today and they say, I'm gonna shrink my data center, I'm gonna focus on, on moving certain things to the cloud, DR and backup and especially DR and backup VMware might be one of the easiest, fastest things to take into the cloud. And the partnership betweens VMware and NetApp might actually give you >>And the ONAP is great solution. Fsx there? Yes. I think you guys got a real advantage here and I want to get into something that's kind of a gloom and doom. I don't have to go negative on this one, Savannah, but they me nervous John. But you know, if you look at the economic realities you got a lot of companies like that are in the back of a Druva, Netta, Druva, cohesive rub. Others, you know, they, you know, there's a, their generational cloud who breaks through. What's the unique thing? Because you know there's gonna be challenges in the economy and customers are gonna vote with their wallets and they start to see as they make these architectural decisions, you guys are in the middle of it. There's not, there may not be enough to go around and the musical chairs might stop or, or not, I'm not sure. But I feel like if there's gonna be a consolidation, what does that look like? What are customers thinking? Backup recovery, cloud. That's a unique thing. You mentioned economics, it's not, you can't take the old strategy and put it there from five, 10 years ago. What's different now? >>Yeah, I think when it comes to data protection, there is a real change in, in the technology landscape that opened the door for a lot of new vendors to come and offer. Should we expect consolidation? I think microeconomic outside and other things will probably drive some of that to happen. I think there is one more parameter, John, that I wanna mention in this context, which is simplicity. Many of the storage vendors, including us, including aws, you wanna make as much of the backup NDR at basically a simple checkbox that you choose together with your main workload. This is another key capabilities that is, that is being, bringing and changing the market, >>But it also needs to move up. So it's not only simplicity, it's also about moving to the applications that you use, use, and just having it baked in. It's not about you going out and finding a replication. It's like what Ronan said, we gotta make it simple and then we gotta bake it into what they use. So one of our most recent acquisitions of Insta Cluster allows us to provide our customers with open source databases and data streaming services. When those sit on top of on tap and they sit on top of spots, infrastructure optimization, you get all that for free through the database that you use. So you don't worry about it. Your database is replicated, it's highly available, and it's running at the best cost. That's where it's going. >>Awesome. >>You also recently purchased Cloud Checker as well. Yes. Do you just purchase wonderful things all the time? We >>Do. We do. We, >>I'm not >>The, if he walk and act around and then we find the best thing and then we, we break out the checkbook, no, but more seriously, it, it rounds out what customers need for the cloud. So a lot of our customers come from storage, but they need to operate the entire cloud around the storage that they have. Cloud Checker gives us that financial visibility across every single dollar that you spend in the cloud and also gives us a better go to market motion with our MSPs and our distributors than we had in the past. So we're really excited about what cloud checker can unlock for us in >>The future. Makes a lot of sense and congratulations on all the extremely exciting things going on. Our final and closing question for our guests on this year's show is we would love your, your Instagram hot take your 32nd hot take on the most important stories, messages, themes of AWS reinvent 2022. Ronan, I'm gonna start with you cause you have a smirk >>And you do it one day ahead of the keynotes, one day ahead with you. >>You can give us a little tease a little from you. >>I think that pandemic or no pandemic face to face or no face to face, the innovation in the cloud is, is actually breaking all records. And I think this year specifically, you will see a lot of focus on data and scale. I think that's, these are two amazing things that you'll see, I think doubling down. But I'm also anxious to see tomorrow, so I'll learn more about it. >>All right. We might have to chat with you a little bit after tomorrow. Is keynotes and whatnot coming up? What >>About you? I think you're gonna hear a lot about cost. How much are you spending? How far are your dollars going? How are you using the cloud to the best of your abilities? How, how efficient are you being with your dollars in the cloud? I think that's gonna be a huge topic. It's on everybody's mind. It's the macro economics situation right now. I think it's gonna be in every session of the keynote tomorrow. All >>Right, so every >>Session. Every session, >>A bulk thing. John, we're gonna have >>That. >>I'm with him. You know, all S in general, you >>Guys have, and go look up what I said. >>Yeah, >>We'll go back and look at, >>I'm gonna check on you >>On that. The record now states. There you go, Kevin. Thank both. Put it down so much. We hope that it's a stellar show for Spotify, my NetApp. Thank you. And that we have you 10 more times and more than just this once and yeah, I, I can't wait to see, well, I can't wait to hear when your predictions are accurate tomorrow and we get to learn a lot more. >>No, you gotta go to all the sessions down just to check his >>Math on that. Yeah, no, exactly. Now we have to do our homework just to call him out. Not that we're competitive or those types of people at all. John. No. On that note, thank you both for being here with us. John, thank you so much. Thank you all for tuning in from home. We are live from Las Vegas, Nevada here at AWS Reinvent with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

>> We're back in Las Vegas at the ARIA for Fal.Con 22, CrowdStrike's big user conference. I'm Dave Vellante and you're watching the cube. Sven Krasser is here as the senior vice president and chief scientist at CrowdStrike and we're going to get a masterclass in AI for security, Sven. Thanks for coming on. Appreciate it. >> Thanks for having me. >> So I love the title. I just, I'm excited to have you on, I understand you were like employee number two or, you know, really early on >> Among the initial nine. Yeah. >> 11 years ago and I think two days you started. >> Yes. >> What was that like? You know, was that, you know, did you know George beforehand or you kind of? >> Yeah, I, I knew I knew George before, like not as well as I know him now. >> Yeah. >> And it, it sounded like a pretty good proposition about what he was having in mind. Like things security wise didn't really work that well back in the day. And we wanted to try something new, like cloud native, data driven, AI, and use that to stop, to stop breaches. So yeah, like it was very exciting. Like you go there, you have nothing there. First day, you open your laptop and you try to reinvent security. >> Yeah. So, I mean, I know he never, he talks about this. I never said we're going to be an AV company. But of course, you know, you start with antivirus and when at an endpoint and known malware, okay. But unknown malware at the time wasn't really being addressed. And if I understand it you guys brought in machine intelligence from the start. Explain that. >> That's that's right. And like, the way we, we looked at it is like, back then we said, you don't have a malware problem. You have an adversary problem. Just like recognizing that it's not malware but there's people behind it that act on objectives that you need to, that you need to counter and you don't want to run after them. You want to be ahead of them. Like that was, that was the approach, like at a very high level that we were taking and you know, now we have it a little bit more summed up and we say, we stop breaches. So like, that's, that's the end result. >> So how do you specifically leverage AI? Which parts of the portfolio, is it across the portfolio and you know, where did it start? How did it evolve? >> Yeah, we are very, we're very data driven. So we are working hard to use the, the proper tools to work with data wherever we can. And AI being one of these, these tools that we like to bring to bear. The, the cloud, the CrowdStrike security cloud at the moment we're doing about roughly 2 trillion events, with a T, per day. Like that, that volume of data, like going through our platform, that that's not something that you can, that you can work with manually, right? So we need, we need to bring the heavy machinery, like that's, that's how we're bringing AI to bear. >> 2 trillion events per day. I mean, there aren't a lot of organizations that see that many events a day. I mean, maybe, maybe some of the hyperscalers possibly. I don't know. That's a... >> Yeah. I think, I think it really allows us to get unprecedented insights into what's actually going on out there in the, in, in the landscape. And, you know, it's, it's like, it's like with a camera or a telescope, the bigger your aperture the fainter signals you can detect. And that's why like, that's why the volume is, is critical. And that's why we, that's why we from the get go, set out to build a cloud native platform so that we can actually aggregate this type of data and analyze it in one spot, basically where where everything comes together that we can draw these connections. >> Will we ever see security without humans? >> I don't, I don't think so. This, this, this notion that machine intelligence is so intelligent that it just takes these jobs over. To me it's more like a tool, right? Like these, these algorithms, they do need to learn from something they need to learn from human expertise. The way at CrowdStrike we have things set up is like our, our human teams our threat hunters, our MDR staff, our incident responders, like whatever they do, we, we are taking these insights and we're feeding them into the AI algorithms. So if there's, if there's a new type of attack and we have an incident response team on the ground and they find something, that gets leveraged put into a database and our AI can learn from that. I, I, I really like that in the keynote, Kevin Mandia actually talked to that, you know. Like get the incident responders out there, get their knowledge, bake it into products. And that that's, that's the approach that we're taking with, with with our AI. >> So in my head, I'm thinking okay, what do humans do better than machines? I mean, humans are creative, right? Machines really aren't creative, right? I mean, and adversaries are very creative. So, so I guess flip side question, what is, what does AI do? What does the machine intelligence do that that humans can't do? Is it scale? Is it just massive volumes? Help us understand what humans do well and machines do well and how they compliment each other. >> Yeah. So AI is, is very good at working with extremely large amounts of data. Again, like cloud native platform, like that's where you get this AI advantage. It can work with data that is a lot more complex like more facets of data. So we talked about XDR here at Fal.Con a lot, right? Like you get data from all these different products, from all these different angles. Like the more different facets you add to that like it becomes overwhelming for the human mind. It's just like so much complexity that a human can put together in their brain. With AI you don't have these limitations. It's just math. It's just like multiplying big matrices and you can work with a lot larger data sets, like those 2 trillion events that we do per day on the on the CrowdStrike security cloud. But also data that is a lot more complex, that has more facets, looks at the problem from different angles. That's where AI is especially useful. >> I want to ask you as a topic I haven't asked anybody this week and I've been meaning to, is, you know there's this concept of, of living off the land, right? Using your own tools against you. How are you able to detect that? Is that cuz of lateral movement or, I mean I'm sure there are many, many factors, but but how are you addressing that problem? That kind of stealthy using your tools against you? >> Yeah, so adversaries, this is, again there's motivated humans behind that. They figured if they drop a malware file on the machine that's an artifact, an indicator of compromise, right? And that can be detected. So they're avoiding dropping files on disc that could be detected or to bring their to bring their own tools. They try to work with the tools that they find on the machines. They need to act on objective though. There's something they want to accomplish. Like they're not, they're not logging in just to, you know, like do nothing. And this is where indicators of attack come in, right? Like we know what their objectives are and we're trying to capture this. We're describing this in an abstract way. What is it that they try to accomplish? That's what indicators of attack describe and when they act on these objectives then we can catch them. >> So I, I think that the the term indicators of attack, I, I, you may have coined it. I'm, I'm not sure. I think it was you announcement at, at black hat. Those indicators are not static, right? To your point, the humans on the other end are motivated. Are you a can, can AI help predict future indicators of attack maybe working with, with humans? >> Yeah, this is, this is something that we recently rolled out where we are connecting our AI intelligence to our indicator of attack framework. Where basically the AI crunches the big data and then the indicators, the, the knowledge that the AI generates, understanding the context of the situation, can feed into the indicators of attack that we're evaluating to see if an adversary is acting on a specific objective. And then if an IOA triggers, that can feed back into the AI and the AI can use that information to derive for more precise results. We have a good feedback loop between these two, these two systems and they're more tightly integrated now. >> As a, as an AI expert, I want to ask you, is is the intelligence, is AI actually artificial? Or is it, is it real? >> Well, it, it is artificial cause I guess we, we build it right? Like it's a human made. I, I think a lot of people get hung up on the term intelligent and it, it's not really intelligent in the say, in the sense that it acts on agency with, with agency like you would look at a problem, right? It's good at solving specific types of tasks and problems that we can define in ways that these algorithms work on it. But it is not the same level of creative thinking that a human brings to the problem. And this is, going back to the beginning of the conversation, this is where we like to have humans involved in the teaching of the AI. The AI connect autonomously in real time stopping threats. But there's humans that take a look at what is going on to give the AI input and feedback and, and improvements because we are up against other humans, right? You don't want to have a human kind of press the buttons of the AI until they found a way around it. But that's called adversarial machine learning. Very real threat as well. Like we are, we're looking at the problem as humans against humans. Like what, what tools do we need to bring to the battle to keep the adversaries out of our customer's networks? >> Okay. So my follow up is, but there are systems of agency for our detection is a, as an example. But your, I think your point is that that never would've been possible without humans. Is that right? Or... >> Yeah, like on, on the one hand, these systems get trained with human knowledge. On the other hand, there, there are humans that take a look at, if the systems give the right responses. Like there, there isn't like if you talk to your smart speaker, like, like for me, like I'm, I'm asking my smart speaker to turn a specific light on in my living room and it, it, half the time doesn't work, right? Like that, that wouldn't happen with a human. There's like a lot more context and understanding and humans are more robust. Like it's, it's harder to fool a human. The limitation that we humans have is complexity, complexity and volume. So we're trying to make like a peanut butter and cookie approach, a peanut butter and chocolate approach rather, where we want to use the human creativity alongside the AI, which can handle scale complexity and volume at unprecedented, unprecedented scales. >> And when you bring it out to the edge, we, we were just talking to Stefan Goldberg about IOT and extended IOT. When you think about, you know, AI, a lot of lot of AI today is modeling that's done in the cloud and then applied. But when you go out to the edge, you you're starting to see more AI inferencing and near realtime, or even real time. Will that change the equation? What's the future of, of, of AI and cyber look like? >> I think, I, I think it would be pervasively applied. So we are using it already on the edge, on our sensors, but also in the cloud, right? On the sensor, we want to be able to act very quickly on the endpoint, want to be able to act very quickly without any delay with local inflammation. Or if the system is offline for a period of time, right? So we have AI models running there. In the cloud, we have the advantage of being able to work with vast amounts of data without slowing down our customer's machines. So like models will be applied everywhere where there's data, like that's kind of the name of the game. Like let's bring, let's bring this, this type of artificial intelligence, this type of, of like refined digested expertise, wherever the data sits on the end point, in the clouds, where you have it. >> And CrowdStrike doesn't care, right? I mean, it's... >> We care about stopping the breaches. >> Yeah. But you're agnostic to the physical location of >> That, that's correct. >> The activity. So last question is, how should we as humans prepare for the future of AI in, in cyber? >> That's a, that's a good question. I, I would say like, stay, stay creative and like figure out how we can get that knowledge that you have like formalized into, into databases, right? AI, the way I look at it is an amplifier of human expertise. You do something at a small scale as a human, the AI system can do it at a big scale, right? Like it's kind of like digging with a spoon whether it's digging with an excavator, with a, with a backhoe. So I I'd say stay, stay creative and see how we can take things that we do as humans in the small scale and let's do it in the cloud, like with with large data volumes. >> Great advice, creativity, I think is, is a key. Sven, thanks so much for coming on the cube. Really appreciate your time. >> Thanks for having me. >> You're very welcome. Okay. Keep it right there. Listen, by, by the way, I meant to to tell our audience a lot of resources at siliconangle.com, thecube.net, wikibon.com, has a ton of research all available at for no charge. No, no, no password needed. Just access that. Check it out. We're live from the ARIA hotel in Las Vegas, Fal.Con 22, Dave Vellante for the cube. We'll be back after this short break. (calming xylophone music)

>>Welcome back everyone to the cubes coverage here in Seattle, Washington for AWS's marketplace seller conference. The big news here is that the Amazon partner network and marketplace coming together and reorganizing into one organization, the AIST partner organization, APO bringing together the best of the partnership and the marketplace to sell through. It's a sellers company. This is the second year, but technically with COVID, I call it a year and a half. This is the cube. I'm John for your host. Got a great guest, Leah for sale vice president of business development at four square. Leah, thanks for coming on the cube. Look great. Yeah. >>Hey, thanks. Thanks for having me here. >>So four square, everyone, and that has internet history knows you. You check in you'd become the mayor of a place right back in the day, all fun. It was a great app and I think it was competitor go sold the Facebook, but that was the beginning of location data. Now you got Uber apps, you got all apps, location, everywhere. Data is big here in the marketplace. They sell data, they got a data exchange, Chris head of marketplaces. Like we have all these things we're gonna bring 'em together, make it simpler. So you're on the data side. I'm assuming you're selling data and you're participating at the data exchange. What is Foursquare doing right now? Yeah, >>Exactly. So we are part of the data exchange. And you mentioned checking in. So we, we are really proud of our roots, the, the four square app, and that's kind of the basis still of our business. We have a hundred million data points, which are actually places of interest across the world 200 countries. And we are we're in the business of understanding whereplace are and how people move through those places over time. And >>What's the value proposition for that data. You're selling the data. >>We are selling the data and we're selling it. You can think about use cases. Like how can I improve the engagement with my app through location data? So for example, next door, as a customer of ours, everyone knows next door. When a new business comes online, they wanna make sure that business is a real business. So they use our places to ensure that the address of that business is accurate. >>So how did you, how do you guys get your data? Because if you don't have the first party app, you probably had critical mass of data. Yeah. But then do other people use your data and then re contribute back in kinda like, well, Stripe is for financial. You guys are plugging in yeah. To >>Apps. A great question. So we still do have our consumer apps. We're still proud of those. It's still a basis of our company really. Okay. So, but we take that data. So our first party data, we also, for all the web, we have some partners integrate our SDK. And so we're pulling in all that data from various sources and then scrubbing it and making sure we have the most unique. >>So you guys still have a business where the app's working. Yep. Okay. But also let's just say, I wanna have a cube app. Yeah. And I want to do a check in button. Yep. So rather than build checking in, could I OEM you could four square is that you >>Could, and we could help you understand where people are checking in. So we know someone's here at the Hilton and Bellevue, we know exactly where that place is. You building the Cub app. You could say, I'm gonna check in here and we are verified. We know that that's the >>Right place. So that's a good for developer if they're building an app. >>Absolutely. So we have an SDK that any developer can integrate. >>Great. Okay. So what's the relationship with the marketplace? Take us through how Foursquare works with AWS marketplace. >>Sure. So we are primarily integrated with ADX, which is sort of a piece of marketplace it's for data specifically, we have both of our main products, which are places that POI database and visits, which is how people move through those places over time. So we're able to say these are the top chains in the country. Here's how people move throughout those. And both those products are listed on ADX. >>So if I'm in Palo Alto and I go to Joe in the juice yeah. You know that I kind of hang in one spot or is it privacy there? I mean, how do you know like what goes on? Well, >>We know somebody does that. We don't >>Know that you do that. So >>We ensure, you know, we're very privacy centric and privacy focused. We're not gonna, we don't tell anybody at you >>Yourself it's pattern data. It is. >>Okay. So it's normalized data, right? Over time groups of people, >>How they, how are people using the data to improve processes, user experience? What are some of the use cases? >>So that example, nextdoor, that's really a use case that we see a lot and that's improving their application. So that nextdoor app to ensure that the ACC, the data's accurate and that as you, as a user, you know, that that business is real. Cuz it's verified by four wear. Another one is you can use our data to make business decisions around where you're gonna place your next loca. You know, your next QSR. So young brands is a customer of ours. Those are, those guys are pizza hut KFC. They work with us to figure out where they should put their next KFC. Yeah. >>I mean retail location, location, location. Yeah. >>Right. Yeah. People are still, even though e-commerce right. People still go into stores >>And still are. Yeah. There's, there's, there's probably lot, a lot of math involved in knowing demographics patterns. Volume. >>Yeah. Some of our key customers are really data scientists. Like the think about cus with businesses that have true data science companies. They're really looking at that. >>Yeah. I mean in, and out's on the exit for a reason. Right. They want in and out. Yeah. So they wanna put it inland. >>Right. And we can actually tell you where that customer from in and out where they go next. Right. So then, you know, oh, they go to this park or they go somewhere and we can help you place your next in and out based on that visitation. >>Yeah. And so it's real science involved. So take us through the customers. You said data scientists, >>Mostly data scientists is kind of a key customer data science at a large corporation, like a QSR that's >>Somebody. Okay. So how is the procurement process on the marketplace? What does the buyer get? >>So what we see the real value is, is because they're already a customer of Amazon. That procurement is really easy, right? All the fulfillment goes through Amazon, through ADX. And what you're buying is either at API. So you can, that API can make real time calls or you're buying a flat file, like an actual database of those hundred points of interest. >>And then they integrate into their tool set. Right. They can do it. So it's pretty data friendly in terms of format. >>You can kind of do whatever you want with it. We're gonna give you that as long as you're smart enough to figure out what to do. Do we have a >>Lot of, so what's your experience with AWS marketplace? I mean, obviously we, we see a lot of changes. They had a reorg partner network merging with marketplace. You've been more on the data exchange, Chris kind of called that out. It's yeah. It's kind of a new thing. And, and he was hinting at a lot of confusion, but simplifying things. Yeah. What's your take of the current AWS marketplace >>Religions? I actually think ADX because our experience has primarily been ADX. I think they've done a really good job. They've really focused on the data and they understand how CU, how, you know, people like us sell our data. It hasn't been super confusing. We've had a lot of support. I think that's what Amazon gives you. You have to put a lot of effort into it, but they're also, they also give you a lot of support. >>Yeah. And, and I think data exchange is pretty significant to the strategic. It is >>Mission. It is. We feel that. Yeah. You know, we feel like they really value us as a partner. >>What's the big thing you're seeing out there right now in data, because like you're seeing a lot more data exchanges going on. There's always been data exchange, but you're seeing a lot more exchanges between companies. So let's just take partners. You're seeing a lot more people handle front end of a, a supply chain and you got more data exchanges. What's the future of data exchanges. If you had to kind of, you know, guess given your history in, in the industry. Yeah. What's the next around the corner trend? >>I think. Well, I think there's a, has to be consolidation. I know everyone's building one, but there's probably too many. I know from our experience, we can't support all of them. We're not a huge company. We can't support Amazon and X and Y and Z. Like it's just too many. So we kind of put all of our eggs in a couple baskets. So I think there'll be consolidation. I think there has to be just some innovation on what data products are, you know, for us, we have these two, it's an API and a flat file. I think as exchanges think about, you know, expanding what are the other types of data products that can help us build? >>Yeah. I mean, one of the things that's, you know, we see, we cover a lot of on the cube is edge. You know, you got, yeah. Amazon putting out new products in regions, you got new wavelength out there, you got regions, you got city level connectivity, data coming from cars. So a lot more IOT data. How do you guys see that folding into your vision of data acquisition and data usage, leverage, reuse, durability. These >>Are, yeah. I mean, we're, we are keeping an eye on all of that. You know, I think we haven't quite figured out how we wanna allocate resources against it, but you know, it's definitely, it's a really interesting space to be in. Like, I don't think data's going anywhere and I think it's really just gonna grow and how people use it's >>Gonna expand. Okay. So if I'm a customer, I go to the marketplace, I wanna buy four square data. What's the pitch. >>We can help you improve your business decisions or your applications through location data. We know where places are and how people move through the world over time. So we can tell you we're, we're sure that this is the Hilton in Bellevue. We know that, that we know how many people are moving through here and that's really the pitch. >>And they use that for whatever their needs are, business improvement, user experience. Yeah. >>Those are really the primary. I mean, we also have some financial use cases. So hedge funds, maybe they're thinking about yeah. How they wanna invest their money. They're gonna look at visits over time to understand what people are doing. Right. The pandemic made that super important. >>Yeah. That's awesome. Well, this is great. Great success story. Congratulations. And thanks for sharing on the cube. Really appreciate you coming on. Thank you. My final question is more about kind of the future. I wanna get your thoughts because your season pro, when you have the confluence of physical and digital coming together. Yeah. You know, I was just talking with a friend about FedEx's earnings, comparing that to say, AWS has a fleet of delivery too. Right? Amazon, Amazon nots. So, but physical world only products location matters. But then what about the person when they're walking around the real world? What happens when they get to the metaverses or, you know, they get to digital, they tend an event. Yeah. How do you see that crossroad? Cuz you have foot in both camps. We do, you got the app and you got the physical world it's gonna come together. Is there thoughts around, you can take your course care hat off and put your industry hat on. Yeah. You wanna answer that? Not officially on behalf of Foursquare, but I'm just curious, this is a, this is the confluence of like the blending of physical and digital. >>Yeah. I know. Wow. I admittedly haven't thought a whole lot about that. I think it would be really weird if I could track myself over time and the metaverse I mean, I think, yeah, as you said, it's >>It's, by the way, I'm not Bo on the metaverse when it's blocked diagrams, when you have gaming platforms that are like the best visual experience possible, right? >>Yeah. I mean, I think it, I think we'll see, I don't, I don't know that I have a >>Prediction, well hybrid we've seeing a lot of hybrid events. Like this event is still intimate VIP, but next year I guarantee it's gonna be larger, much larger and it's gonna be physical and face to face, but, but digital right as well. Yeah. Not people experiencing the, both that first party, physical, digital hybrid. Yeah. And it's interesting something that we track a lot >>Of. Yeah, for sure. Yeah. I think we'll have a, well, I think we'll, there's something there for us. I think that those there's a play there as we watch kind >>Of things change. All right, Leah, thank you for coming on the Q appreciate so much it all right. With four Graham, John fur a year checking in with four square here on the cube here at the Amazon web services marketplace seller conference. Second year back from the pandemic in person, more coverage after this break.

(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)

>>Hey everyone. Welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four of our ongoing series that features exciting startups within the AWS ecosystem. This episode's theme, cybersecurity protect and detect against threats. I'm your host, Lisa Martin, and I'm pleased to welcome back. One of our alumni chase joins me the principal strategist at jump cloud chase. It's great to have you back on the >>Perfect Michael, thank you so much for having me again, >>Tell the audience just a little quick refresher on jump cloud, open directory platform. We just give them that little bit of context. >>You bet. So jump cloud provides an open directory platform and what we mean by that is we help manage all of your employees, identities, the devices that they operate on, and then all the access that they need in order to get their work done in a modern it environment. >>So from a target, a market segment perspective, this is really targeted at small medium enterprise SMEs managed security providers. MSPs, talk to me a little bit about that and some of the what's in it for me, for those folks. >>Yeah, absolutely. And when we are thinking about specifically within that market, so small, medium enterprises and the it, or the managed service providers that help support those organizations, there's a lot of different technologies that you use in order to make sure that you have a secure organization. And within that group specifically, there's a lot less of a luxury right of an enterprise budget or kind of all these different personnel that you might have available to you. And it's really kind of down to maybe one team or just a couple folks or just one person wearing a lot of different hats. And so we've designed the open directory platform to help accommodate for a lot of those different pieces where we're bringing in multiple different types of technologies from identity access management, device management and MDM, MFA access through single sign on all of those different pieces and more that help kind of come into one platform. >>So not only do you have all the technology there at your disposable, but also all the visibility and analytics of folks that are getting in and just trying to get their job done. But now all of those pieces are, are consolidated into one platform and it really helps support a lot of those organizations, right? And keep in mind, you know, small, medium businesses are the most common businesses, not everyone's coming in from an enterprise. And so here we're able to layer on levels of security and making sure that you have best practices, no matter what size you're operating in. >>So consolidating it management, securing employees, access to a variety of it. Resources is really kind of in a nutshell. >>Absolutely. And just making sure that you're combining that combination of securely accessing all the things that you need, but also making sure that from an end user perspective, it's really easy and you have all those things kind of built in from the get go. >>So how are SSEs and MSPs leveraging jump cloud right now? What are some of the outcomes that you are helping them to achieve? Anything stand out to you? >>I think there's a couple different areas that we help support organizations. One is you can think about just the whole employee life cycle. So when, when someone joins an organization from onboarding, you know, where does that identity come from? How can we make sure that they're productive, you know, effective human beings as they come into it, but then the whole life cycle, as they're accessing or changing resources within their role, all the way to the end, where they might be leaving the organization and we can securely off board that person. And so that whole flow that you might have from an organization standpoint is one aspect. Another area is as companies continue to grow, they might be going after, you know, maybe audits, level compliance, other pieces that might help them grow. And there's a lot of layers that you need to think about or different types of technologies and processes to have those certifications and credentials. >>And so we help support those organizations again, by consolidating all those different technologies into one spot. It makes it a lot easier for people to get up to par in how they think that their security standards should be set within an organization. And finally too, I'd say just ease of mind. There's a lot of pieces when you're thinking about, you know, where people might be coming in from how do I get visibility into all those different aspects? And when you have all that under one roof, it adds a lot of, I'd say, you know, less mental stress in terms of one, how all those technologies should be working together effectively, also securely, but then also making sure that you have time in the day to tackle big projects and let some of the, let's say, run rate security out of the way. >>Yeah. That's really important to be able to assign resources that are able to make the biggest impact across the organization, moving things off the plate that are not necessary or more mundane twice a year. I understand jump cloud does a survey with SMEs where you really are aimed at understanding kind of where they are in the market today, their concerns, trends, challenges, budgets. Then I saw you just published results from a survey in June of 2022. Talk to me a little bit about the demographics of the survey, who, who are you talking to within SMEs? And then we can kind of crack open some of those really interesting findings that came out this year. >>Yeah. So we love to get a pulse check of what's happening within the industry, but specifically within that small, medium size, if you will. And so for that survey that we ran, we talked to 400 different roles, kind of that touch it from security. So from vice president of the CCSO all the way down to it, admins and anyone else in between, and we're really looking at organizations that had about 500 employees or less, cuz there's a lot of information out there, especially from the enterprise of, you know, Hey, here's best practices. Here's all the things that you can do. But for smaller organizations, it's not as clear cut or you have less of an understanding of what your peers might be going through or kind of what their concerns are. And so when we're running that survey, that's one thing that we like to keep in mind is it's really meant for organizations at that size because there's, there's some commonalities that you start to see in suss out. >>And it's not to say that those aren't the same concerns that the enterprise folks have as well, because a lot of the things that will come out, you know, they are security based say, Hey, what's top of mind, or what's kind of keeping you up at night. There were some clear indicators and especially well from kind of, as we do this survey, you know, every six months or kind of even year over year, you start to see some trends that are emerging. And so a, a lot of the big ones are, you know, ransomware software, vulnerability and network security. Those are kind of the top three aspects when we're looking at, Hey, what are specifics that are keeping you up? And those are easy to say because ransomware is obviously in the news. Even this week, there are three different organizations just kind of pick out. >>So brussel who does dental manufacturing, they had ransomware in trust, which is another cybersecurity organization. They were breached. But then also Fremont county here in Colorado as a government organization, all three of those were hit by ransomware. And you might not say, Hey, there's, you know, they're all kind of random and they're not put together, but under the hood really it's a lot of the same different technologies that are powering, how people get access into things. Do they have the right levels of credentials? Are there conditions set within that type of access, especially if it's privilege. And so you start to consolidate and bubble down all those different things that can lead up to those concerns. And then even on the software vulnerability side, Mac release, two different vulnerabilities this week. And so now it quickly becomes, okay, great. How can I make sure that my employees are using not only a secure device, but a secure device, that's up to date because it's a dynamic field as all of these things coming through. >>And these are a lot of the gotchas that can keep, you know, small, medium enterprises up at night because if something happens a security event like that, it could be a, you know, a career ending event, but also a company ending event. When you think about that. And so that becomes a really high level of importance because no one wants to see their name in the news, but it also takes a lot of different steps in order to create the layers that are necessary in order to achieve, you know, really solid round stand on for organization to do that. And so that's where we like to come in and help and making sure that a lot of those layers are actually easier to implement than you thought. And it's not this huge project, but you're doing it in a way that's conscious and also not really getting the way of kind of battling users or making sure that their experience is a nightmare as well in order to achieve these goals that you have as an organization, >>You bring up ransomware, it's become a household term that I think probably every generation alive right now in some form or fashion understands what it is to a, to some degree it's now security threats in general. Now no longer if we get hit, it's a matter of one. You gave three great examples of SMEs that were hit recently and organizations. We wouldn't think really them everybody's vulnerable. You talked about the different, you know, some of the, the concerns, software, vulnerable vulnerability, exploits, the use of unsecured networks, people, and this is so common using the same password across applications that SSEs and enterprises too are dealing with. They have to be able to lean on MSPs, for example, in the SME space to say, help us with these obvious vulnerabilities, we need to make sure that our employees are productive. They're working together. We can onboard and offboard people in a secure way. How did this survey uncover how SMEs are leaning more on MSPs to help solve some of those risks that you've talked about? >>I think one of the more interesting trends that we've seen is just the ability and the ramp for organizations to lean on managed service providers. You saw a lot of this during kind of the, the beginning of the pandemic or kind of this really shift to remote work where people kind of have this mentality of, okay, it might be a cost center and, and will have, but it it's always felt this importance to making sure that people are on site. They understand their culture. They understand the, the ways that the organization works. However, now, a lot more organizations are stepping back and saying, well, if I can't see anyone in the office or if there's only half or maybe 10% that are showing up, you know, are there other economies of scale almost that I can get from leveraging a managed service provider bringing in other expertise, right? >>And so it might be valuable to say, Hey, it's not only just managing my organization, but five others. And so now you can start to see and kind of lean on best practices that they've evolved over time. And I think one of the more interesting stats is we see that, you know, almost nine out of 10 organizations that we surveyed are either leveraging an MSP or have considered it. And one of those things that's actually pulling them back or some organizations say, Hey, I've looked at it, but I'm not quite ready to commit to outsourcing this section of my organization that, or kind of bringing in someone to manage it fully alongside with me almost in a co-managed type of environment is a third of 'em say, Hey, I, I don't know how secure the MSPs are themselves. How do they think about their own internal practices? >>And what does that look like? Because again, you, you're thinking about handing over the crown jewels over to someone and say, Hey, here's some of our, our most vulnerable or critical assets that we need to have secured and, and making sure that that's part of the organization. And so it's a, it's an honest conversation that a lot of owners have with MSPs and say, look, are, are you up to snuff, right? Because if something happens, sure, I might have one person to go after, or you might have SLAs that I can, I can go. But it still means me as an organization has been targeted. What does that look like in our types of relationship? And so a lot of the partners that we have on the jump outside, it's a very common conversation that they have with our clients and saying, walking them through and say, Hey, here's our, our security plan. >>Here's how we approach that. Here's all the different tools that we have at, at our disposal that are working alongside jump cloud in order to make sure that not only do you have good posture, I'd say good areas where the organization is set up for success, where you're thinking about not sharing passwords or there's password complexity, or there's other technologies like single sign on that, help reduce that. But in addition to what type of network scanning do you have available? What type of antivirus do you leverage? What are all the other pieces that create that holistic security structure? And so sometimes it's a lot easier for MSPs to deliver that and package it up instead of having, you know, an overburdened it, admin said, great, this is another project that I have to go through and think about and look at pricing and kind of other those components, because it helps speed up. I'd say your time to being more secure. And that's a really real conversation for organizations as they think about planning, as they think about budgets and what impact that might have on organization, making sure that employees can get work done. But we're also thinking about in a very secure mindset within the organization. >>That's so critical as we talked about every or every organization of every size in every industry is vulnerable. There's just no weight getting around it. These days. You talked about an interesting stat, about 90% of the SME surveyed some written we're yes, we're relying on MSV, but we still worry about security. Talk to me from the jump cloud, AWS perspective. How do you help though? That's cause that's a big number, the 90% of SMEs that are still concerned about security, how do you help them dial that down? >>I think it's really understanding, you know, you mentioned AWS, so what are the critical access and what are those points that look like that we need to get a handle on? And how can we make that easier? Cause I think one of the pieces that will often come at and say, Hey, we really wanna make this approach work. We really wanna make sure that when you, when you wake up and you need to get into Q and a environments or, or production or whatever, that might be, that it's a seamless experience, but we as an organization have visibility into what's going on and Hey, if you're getting promoted or your role is changing, we wanna make sure that those attributes or kind of those pieces that are associated to you and your identity are changing with it. And so making sure that there's this dynamic motion available to folks, as they start thinking about, you know, where a majority of their IP lives, it's no longer in some server closet and yes, it might still be on a, on a manufacturing floor, but it's those components that become the most critical for organizations you've heard, I'd say, you know, certainly within the last five years and probably even goes further back where a lot of traditional organizations say, Hey, we're a software company now we're, you know, kind of insert for innovation, making sure we can do that. >>And I think a lot of organizations are still going through that transition, but right behind it and what's coming next. And certainly a lot of organizations start to say, not only are we a software company, but we're a security company. And with that, that comes the mindset. Not only of here's how we tactically get into the things that we need to do our job, but the why behind it. And I think that's one of the elements that might be missing or is certainly one of, I know that we have a lie attainment kind of take that approach of, yes, we're gonna be implementing, we need to have your device passion updated because there's vulnerabilities. But for everyone else kind of on the end user side, it's like, well, okay, well why, why do we need to do that? And so by having that security first type of mentality, that allows everyone to be on the same page, play on the same team and making sure that when, you know, those requests are coming in both back and forth between end users and its security team, anyone else that might be involved within that process, you all understand that say, Hey, it's not, you know, it, it's not my job. >>It's everyone's job, right? We're all in this together because that's some of the parts where it can start to fall down too. You might have a team that has the best practices and in, you know, in intentions, but if the implementation and the follow through isn't bought in from everyone, then you're also playing against the speed of the organization to adopt it. And that's really the timeline that you're battling, especially when you're thinking about ransomware or someone who already might be in it is how can we help mitigate a lot of those different pieces. So by combining all those different elements into a thought process, into a mentality of being a security first organization, that's really kind of helps within the ripple effect all the way down into, you know, the critical resources like AWS. >>It has to be a holistic view. There's really no other choice these days. And it also has to be done in a timely fashion. What did, as we wrap up kind of talking about the survey here, what were some of the trends, the future trends it uncovered as we are still in a remote and distributed work environment. It probably always will be. We've seen challenges and everyone's mental health in terms of, of strapped resources. What did the survey uncover as to what these folks saw as future trends? >>So I'd say there's a, there's a couple, there there's a lot, but we'll break it down and say, I'd say three core trends that you saw across every organization that we talked to, including our own base of over 180,000 organizations that rely on gem cloud is, Hey, security is number one, right? And we we've talked to that about at length device management is another extension of that. I'm sorry, making sure that, Hey, this is the only piece of hardware I have from the company in front of me. I wanna make sure that I can manage secure it, make sure it's patched as well as we kind of operate in this dynamic and environment, making sure that we're resilient as an organization. And then I'd say finally, as those pieces start to evolve, there's still some organizations that are how trying to understand kind of truly manage what does hybrid and remote and kind of what does that look like for me as an organization? >>Cause I think we're now out of this panic mode and now organizations are now setting up. Okay, what are some of the long term structures as I think about that, and you hear a lot about too, from other organizations that are mandating folks to come back or okay. Maybe it's just a couple days a week or all of those decisions have impacts on the it organization. So that is very alive and well, I'd say one of the other pieces you mentioned mental health is that we are starting to understand a little bit more, you know, kind of who's behind the computer. Who's, who's behind the keyboard. What does the impact have for them? Because in this type of work environment as well, you know, it's still challenging to find really good talent. And so you might be strapped for resources. You might be the only person that's trying to implement these processes or the security protocol, or trying to help get us up into a good compliance posture, all of those different pieces kind of on it. >>And so you can start to think about man, how do I, how do I make progress? And I think that's one of the other pieces that is really important for folks kind of from that perspective is, you know, always understand that you're making progress, even though the, the tickets might be coming at you and you, there's never ending in sight. All those steps that you take for an organization are critically important. And so, and it's not always just a people answer cuz you might, might not be in the position to say, Hey, we need an extra five hands on this in order to make it done. It might have to be more of a conversation of, Hey, here are the pieces that we need to automate. Here are the business processes that we really need to think about in order to have a fundamental impact on what we can do. >>And then you can come back and say, great. And if we have this, it might actually look like one and a half people. You can't really hire a half person, but you come into those types of mentality with a really solid argument of here's what we need to have in order to make this happen. And I think too, getting that type of buy-in again, making sure, Hey, we are a security company after all, we're all in this together that allows everyone to kind of help pitch in because if you don't have that piece, then you know, everything can feel much more burdensome, right? And the level of burnout increases the, the level of mental health in general, across the teams that are acting as supporting functions for an organization, start to get burnout. And it might not always be as Hey, as important as, as revenue or Hey, we're getting this marketing campaign out, but it's this underwriting thing in terms of really, truly important infrastructure that the company needs to think about. >>And when you can involve all of those different pieces, then people feel like they can make a positive impact. They feel more empowered. They have, you know, emojis attached to tickets and say, Hey, it was so great to help you out today. And a lot of those I'd say interpersonal connections that you might be missing in a remote only type of world in organization. And so bringing all those little tidbits back into, you know, how to, how to be a good person, how to be a good human and how to make sure that there's some personality involved with it. And it's not just this ongoing process. I think there's a little bit of give and take, but that's one other thing that we've surfaced is really just understanding a better picture of who's implementing all these amazing things around the world. >>That's so important. There's so many different levers to the pull here where becoming a security company is concerned. Where can folks go to one chase, get the surveying two, some final thoughts. What, where can folks go to actually test out jump drive? >>Yeah, absolutely >>Jump out. Excuse me. >>So within everything that we talked about, some from various different technologies from identity management, device management, SSO, MFA, and many, many more. So you can go to jumpcloud.com, create a free organization. It's free up to 10 users, 10 devices. So even for really small organizations, even if you're a startup, we can help leverage enterprise grade security technology for you to implement as well as more detailed on the reports. And so if you wanna get a better sense of kind of how we look at the world types of information that we can bring back and making sure that you're learning from your peers and how to implement and put your best foot forward within the organization, we always have a ton of amazing resources and content that really looks at, you know, who's doing the work. Why are they doing the work? And how is that work impactful within multiple different organizations and not only just the organizations themselves, but those that are supporting it like managed service providers of the world. >>Got it. Awesome. Chase. Thank you so much for joining me on this episode of the AWS startup showcase, talking to us about what jump cloud is uncovered with respect to the concerns that SMEs have, how MSPs are helping, how jump cloud is also a facilitator of really helping to organizations to become security organizations. We appreciate your time. >>Absolutely. Thank you so much for having me again. >>Our pleasure. We wanna you for watching. Keep it right here on the, for more action. The, is your leader in live coverage?

>> From theCUBE Studios in Palo Alto and Boston bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> After a two year hiatus, AWS re:Inforce is back on as an in-person event in Boston next week. Like the All-Star break in baseball, re:Inforce gives us an opportunity to evaluate the cyber security market overall, the state of cloud security and cross cloud security and more specifically what AWS is up to in the sector. Welcome to this week's Wikibon cube insights powered by ETR. In this Breaking Analysis we'll share our view of what's changed since our last cyber update in May. We'll look at the macro environment, how it's impacting cyber security plays in the market, what the ETR data tells us and what to expect at next week's AWS re:Inforce. We start this week with a checkpoint from Breaking Analysis contributor and stock trader Chip Simonton. We asked for his assessment of the market generally in cyber stocks specifically. So we'll summarize right here. We've kind of moved on from a narrative of the sky is falling to one where the glass is half empty you know, and before today's big selloff it was looking more and more like glass half full. The SNAP miss has dragged down many of the big names that comprise the major indices. You know, earning season as always brings heightened interest and this time we're seeing many cross currents. It starts as usual with the banks and the money centers. With the exception of JP Morgan the numbers were pretty good according to Simonton. Investment banks were not so great with Morgan and Goldman missing estimates but in general, pretty positive outlooks. But the market also shrugged off IBM's growth. And of course, social media because of SNAP is getting hammered today. The question is no longer recession or not but rather how deep the recession will be. And today's PMI data was the weakest since the start of the pandemic. Bond yields continue to weaken and there's a growing consensus that Fed tightening may be over after September as commodity prices weaken. Now gas prices of course are still high but they've come down. Tesla, Nokia and AT&T all indicated that supply issues were getting better which is also going to help with inflation. So it's no shock that the NASDAQ has done pretty well as beaten down as tech stocks started to look oversold you know, despite today's sell off. But AT&T and Verizon, they blamed their misses in part on people not paying their bills on time. SNAP's huge miss even after guiding lower and then refusing to offer future guidance took that stock down nearly 40% today and other social media stocks are off on sympathy. Meta and Google were off, you know, over 7% at midday. I think at one point hit 14% down and Google, Meta and Twitter have all said they're freezing new hires. So we're starting to see according to Simonton for the first time in a long time, the lower income, younger generation really feeling the pinch of inflation. Along of course with struggling families that have to choose food and shelter over discretionary spend. Now back to the NASDAQ for a moment. As we've been reporting back in mid-June and NASDAQ was off nearly 33% year to date and has since rallied. It's now down about 25% year to date as of midday today. But as I say, it had been, you know much deeper back in early June. But it's broken that downward trend that we talked about where the highs are actually lower and the lows are lower. That's started to change for now anyway. We'll see if it holds. But chip stocks, software stocks, and of course the cyber names have broken those down trends and have been trading above their 50 day moving averages for the first time in around four months. And again, according to Simonton, we'll see if that holds. If it does, that's a positive sign. Now remember on June 24th, we recorded a Breaking Analysis and talked about Qualcomm trading at a 12 X multiple with an implied 15% growth rate. On that day the stock was 124 and it surpassed 155 earlier this month. That was a really good call by Simonton. So looking at some of the cyber players here SailPoint is of course the anomaly with the Thoma Bravo 7 billion acquisition of the company holding that stock up. But the Bug ETF of basket of cyber stocks has definitely improved. When we last reported on cyber in May, CrowdStrike was off 23% year to date. It's now off 4%. Palo Alto has held steadily. Okta is still underperforming its peers as it works through the fallout from the breach and the ingestion of its Auth0 acquisition. Meanwhile, Zscaler and SentinelOne, those high flyers are still well off year to date, with Ping Identity and CyberArk not getting hit as hard as their valuations hadn't run up as much. But virtually all these tech stocks generally in cyber issues specifically, they've been breaking their down trend. So it will now come down to earnings guidance in the coming months. But the SNAP reaction is quite stunning. I mean, the environment is slowing, we know that. Ad spending gets cut in that type of market, we know that too. So it shouldn't be a huge surprise to anyone but as Chip Simonton says, this shows that sellers are still in control here. So it's going to take a little while to work through that despite the positive signs that we're seeing. Okay. We also turned to our friend Eric Bradley from ETR who follows these markets quite closely. He frequently interviews CISOs on his program, on his round tables. So we asked to get his take and here's what ETR is saying. Again, as we've reported while CIOs and IT buyers have tempered spending expectations since December and early January when they called for an 8% plus spending growth, they're still expecting a six to seven percent uptick in spend this year. So that's pretty good. Security remains the number one priority and also is the highest ranked sector in the ETR data set when you measure in terms of pervasiveness in the study. Within security endpoint detection and extended detection and response along with identity and privileged account management are the sub-sectors with the most spending velocity. And when you exclude Microsoft which is just dominant across the board in so many sectors, CrowdStrike has taken over the number one spot in terms of spending momentum in ETR surveys with CyberArk and Tanium showing very strong as well. Okta has seen a big dropoff in net score from 54% last survey to 45% in July as customers maybe put a pause on new Okta adoptions. That clearly shows in the survey. We'll talk about that in a moment. Look Okta still elevated in terms of spending momentum, but it doesn't have the dominant leadership position it once held in spend velocity. Year on year, according to ETR, Tenable and Elastic are seeing the biggest jumps in spending momentum, with SailPoint, Tanium, Veronis, CrowdStrike and Zscaler seeing the biggest jump in new adoptions since the last survey. Now on the downside, SonicWall, Symantec, Trellic which is McAfee, Barracuda and TrendMicro are seeing the highest percentage of defections and replacements. Let's take a deeper look at what the ETR data tells us about the cybersecurity space. This is a popular view that we like to share with net score or spending momentum on the Y axis and overlap or pervasiveness in the data on the X axis. It's a measure of presence in the data set we used to call it market share. With the data, the dot positions, you see that little inserted table, that's how the dots are plotted. And it's important to note that this data is filtered for firms with at least 100 Ns in the survey. That's why some of the other ones that we mentioned might have dropped off. The red dotted line at 40% that indicates highly elevated spending momentum and there are several firms above that mark including of course, Microsoft, which is literally off the charts in both dimensions in the upper right. It's quite incredible actually. But for the rest of the pack, CrowdStrike has now taken back its number one net score position in the ETR survey. And CyberArk and Okta and Zscaler, CloudFlare and Auth0 now Okta through the acquisition, are all above the 40% mark. You can stare at the data at your leisure but I'll just point out, make three quick points. First Palo Alto continues to impress and as steady as she goes. Two, it's a very crowded market still and it's complicated space. And three there's lots of spending in different pockets. This market has too many tools and will continue to consolidate. Now I'd like to drill into a couple of firms net scores and pick out some of the pure plays that are leading the way. This series of charts shows the net score or spending velocity or granularity for Okta, CrowdStrike, Zscaler and CyberArk. Four of the top pure plays in the ETR survey that also have over a hundred responses. Now the colors represent the following. Bright red is defections. We're leaving the platform. The pink is we're spending less, meaning we're spending 6% or worse. The gray is flat spend plus or minus 5%. The forest green is spending more, i.e, 6% or more and the lime green is we're adding the platform new. That red dotted line at the 40% net score mark is the same elevated level that we like to talk about. All four are above that target. Now that blue line you see there is net score. The yellow line is pervasiveness in the data. The data shown in each bar goes back 10 surveys all the way back to January 2020. First I want to call out that all four again are seeing down trends in spending momentum with the whole market. That's that blue line. They're seeing that this quarter, again, the market is off overall. Everybody is kind of seeing that down trend for the most part. Very few exceptions. Okta is being hurt by fewer new additions which is why we highlighted in red, that red dotted area, that square that we put there in the upper right of that Okta bar. That lime green, new ads are off as well. And the gray for Okta, flat spending is noticeably up. So it feels like people are pausing a bit and taking a breather for Okta. And as we said earlier, perhaps with the breach earlier this year and the ingestion of Auth0 acquisition the company is seeing some friction in its business. Now, having said that, you can see Okta's yellow line or presence in the data set, continues to grow. So it's a good proxy from market presence. So Okta remains a leader in identity. So again, I'll let you stare at the data if you want at your leisure, but despite some concerns on declining momentum, notice this very little red at these companies when it comes to the ETR survey data. Now one more data slide which brings us to our four star cyber firms. We started a tradition a few years ago where we sorted the ETR data by net score. That's the left hand side of this graphic. And we sorted by shared end or presence in the data set. That's the right hand side. And again, we filtered by companies with at least 100 N and oh, by the way we've excluded Microsoft just to level the playing field. The red dotted line signifies the top 10. If a company cracks the top 10 in both spending momentum and presence, we give them four stars. So Palo Alto, CrowdStrike, Okta, Fortinet and Zscaler all made the cut this time. Now, as we pointed out in May if you combined Auth0 with Okta, they jumped to the number two on the right hand chart in terms of presence. And they would lead the pure plays there although it would bring down Okta's net score somewhat, as you can see, Auth0's net score is lower than Okta's. So when you combine them it would drag that down a little bit but it would give them bigger presence in the data set. Now, the other point we'll make is that Proofpoint and Splunk both dropped off the four star list this time as they both saw marked declines in net score or spending velocity. They both got four stars last quarter. Okay. We're going to close on what to expect at re:Inforce this coming week. Re:Inforce, if you don't know, is AWS's security event. They first held it in Boston back in 2019. It's dedicated to cloud security. The past two years has been virtual and they announced that reinvent that it would take place in Houston in June, which everybody said, that's crazy. Who wants to go to Houston in June and turns out nobody did so they postponed the event, thankfully. And so now they're back in Boston, starting on Monday. Not that it's going to be much cooler in Boston. Anyway, Steven Schmidt had been the face of AWS security at all these previous events as the Chief Information Security Officer. Now he's dropped the I from his title and is now the Chief Security Officer at Amazon. So he went with Jesse to the mothership. Presumably he dropped the I because he deals with physical security now too, like at the warehouses. Not that he didn't have to worry about physical security at the AWS data centers. I don't know. Anyway, he and CJ Moses who is now the new CISO at AWS will be keynoting along with some others including MongoDB's Chief Information Security Officer. So that should be interesting. Now, if you've been following AWS you'll know they like to break things down into, you know, a couple of security categories. Identity, detection and response, data protection slash privacy slash GRC which is governance, risk and compliance, and we would expect a lot more talk this year on container security. So you're going to hear also product updates and they like to talk about how they're adding value to services and try to help, they try to help customers understand how to apply services. Things like GuardDuty, which is their threat detection that has machine learning in it. They'll talk about Security Hub, which centralizes views and alerts and automates security checks. They have a service called Detective which does root cause analysis, and they have tools to mitigate denial of service attacks. And they'll talk about security in Nitro which isolates a lot of the hardware resources. This whole idea of, you know, confidential computing which is, you know, AWS will point out it's kind of become a buzzword. They take it really seriously. I think others do as well, like Arm. We've talked about that on previous Breaking Analysis. And again, you're going to hear something on container security because it's the hottest thing going right now and because AWS really still serves developers and really that's what they're trying to do. They're trying to enable developers to design security in but you're also going to hear a lot of best practice advice from AWS i.e, they'll share the AWS dogfooding playbooks with you for their own security practices. AWS like all good security practitioners, understand that the keys to a successful security strategy and implementation don't start with the technology, rather they're about the methods and practices that you apply to solve security threats and a top to bottom cultural approach to security awareness, designing security into systems, that's really where the developers come in, and training for continuous improvements. So you're going to get heavy doses of really strong best practices and guidance and you know, some good preaching. You're also going to hear and see a lot of partners. They'll be very visible at re:Inforce. AWS is all about ecosystem enablement and AWS is going to host close to a hundred security partners at the event. This is key because AWS doesn't do it all. Interestingly, they don't even show up in the ETR security taxonomy, right? They just sort of imply that it's built in there even though they have a lot of security tooling. So they have to apply the shared responsibility model not only with customers but partners as well. They need an ecosystem to fill gaps and provide deeper problem solving with more mature and deeper security tooling. And you're going to hear a lot of positivity around how great cloud security is and how it can be done well. But the truth is this stuff is still incredibly complicated and challenging for CISOs and practitioners who are understaffed when it comes to top talent. Now, finally, theCUBE will be at re:Inforce in force. John Furry and I will be hosting two days of broadcast so please do stop by if you're in Boston and say hello. We'll have a little chat, we'll share some data and we'll share our overall impressions of the event, the market, what we're seeing, what we're learning, what we're worried about in this dynamic space. Okay. That's it for today. Thanks for watching. Thanks to Alex Myerson, who is on production and manages the podcast. Kristin Martin and Cheryl Knight, they helped get the word out on social and in our newsletters and Rob Hoff is our Editor in Chief over at siliconangle.com. You did some great editing. Thank you all. Remember all these episodes they're available, this podcast. Wherever you listen, all you do is search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. You can get in touch with me by emailing avid.vellante@siliconangle.com or DM me @dvellante, or comment on my 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 in Boston next week if you're there or next time on Breaking Analysis (soft music)

(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

(upbeat music) >> Okay, welcome back everyone. The cube coverage of AWS re:Mars, 2022. I'm John Furrier, host of theCUBE. We got Eric Foellmer, vice president of marketing at Boston Dynamics. Famous for Spot. We all know, we've seen the videos, zillion views. Mega views all over the internet. The dog robotics, it's famous. Rolls over, bounces up and down. I mean, how many TikTok videos are out there? Probably a ton. >> Oh, Spot is- Spot is world famous (John laughs) at this point, right? So it's the dance videos, and all the application videos that we have out there. Spot is become has become world famous. >> Eric, thanks for joining us on theCUBE here at re:Mars. This show really is back. There was still a pandemic hiatus there. But it's not a part of the re's. It's re Mars, reinforcement of security, and then reinvent the flagship show for AWS. But this show is different. It brings together a lot of disciplines. But it's converging in on what we see as the next general- Industrial space is a big poster child for that. Obviously in space, it's highly industrial, highly secure. Machine learning's powering all the devices. You guys have been in this, I mean a leader, in a robotics area. What's this show about? I mean, what's really happening here. What if you had to boil the essence of the top story of what's happening here? What would it be? >> So the way that I look at this show is it really is a convergence of innovation. Like this is really just the cutting edge of the innovation that's really happening throughout robotics, but throughout technology in general. And you know, part of this cultural shift will be to adopt these types of technologies in our everyday life. And I think if you ask any technology specialist here or any innovator here or entrepreneur. They'll tell you that they want their technologies to become ubiquitous in society, right? I mean, that's really what everyone is sort of driving towards from the perspective of- >> And we, and we got some company behind it. Look at this. >> Oh, there we go. >> All right. >> There's a (Eric laughs) There's one of our Spots. >> It's got one of those back there. All right so sorry to interrupt, got a little distracted by the beautiful thing there. >> So they're literally walking around and literally engulfing the show. So when I look at the show, that's what I see. >> Let's see the picture of- >> I see the future of technology. >> Get a camera on our photo bomb here going on. Get a photo bomb action. (Eric chuckles) It's just super exciting because it really, it humanizes, it makes you- Everyone loves dogs. And, you know, I mean, people have more empathy if you kicked Spot than, you know, a human. Because there's so much empathy for just the innovation. But let's get into the innovation because let's- The IOT tech scene has been slow. Cloud computing Amazon web services, the leader hyper scaler. They dominated the back office you know, data centers, all the servers, digital transformation. Now that's coming to the edge. Where robotics is now in play. Space, material handling, devices for helping people who are sick or in healthcare. >> Eric: Mhm. >> So a whole surge of revolutionary or transitionary technologies coming. What's your take on that? >> So I think, you know, data has become the driving force behind technology innovation. And so robotics are an enabler for the tech, for the data collection that is going to drive IOT and manufacturing 4.0 and other important edge related and, you know, futuristic technology innovations, right? So the driver of all of that is data. And so robots like Spot are collectors of data. And so instead of trying to retrofit a manufacturing plant, you know, with 30, 40, 50 year old equipment in some cases. With IOT sensors and, you know, fixed sensors throughout the network. We're bringing the sensors to the equipment in the form of an agile mobile robot that brings that technology forward and is able to assess. >> So explain that a little slower for me. So the one method would be retrofitting all the devices. Or the hardware currently installed. >> Eric: Sure. >> Versus almost like having a mobile unit next to it, kind of thing. Or- >> Right. So, I mean, if you're looking at antiquated equipment which is what most, you know, manufacturing plants are running off of. It's not really practical or feasible to update them with fixed sensors. So sensors that specifically take measurements from that machine. So, we enable Spot with a variety of sensors from audio sensors to listen for audio anomalies. Thermal detectors, to look for thermal hotspots in equipment. Or visual detectors, where it's reading analog gauges, that sort of thing. So by doing that, we are bringing the sensors to the machines. >> Yeah. >> And to be able to walk anywhere where a human can walk throughout a manufacturing plant. To inspect the equipment, take that reading. And then most importantly upload that to the cloud, to the users >> It's a service dog. >> you can apply some- >> It's a service dog. >> It really is. And it serves data for the understanding of how that equipment is operated. >> This is big agility for the customer. Get that data, agile. Talk about the cost impact of that, just alone. What the alternative would be versus say, deploying that scenario. Because I'd imagine the time and cost would be huge. >> Well, if you think, you know, about how much manufacturing facilities put into the predictive maintenance and being able to forecast when their equipment needs maintenance. But also when pieces of equipment are going to fail. Unexpected downtime is one of the biggest money drains of any manufacturing facility. So the ability to be able to forecast and get some insight into when that equipment is starting to perform less than optimally and start to degrade. The ability to forecast that in advance is massive. >> Well I think you just win on just in retrofit cost alone, nevermind the downside scenarios of manufacturing problems. All right, let's zoom out. You guys have been pioneers for a long time. What's changed in your mind now versus just a few years ago. I mean, look at even 5, 10 years ago. The evolution, cost and capability. What's changed the most? >> Yeah, I think the accessibility of robots has really changed. And we're just on the beginning stages of that evolution. We really are. We're at the precipice right now of robots becoming much more ubiquitous in people's lives. And that's really our foundation as a company. Is we really want to bring robots to mankind for the good of humanity, right? So if you think about, you know, taking humans out of harm's way. Or, you know, putting robots in situations where, you know, where it's assessing damage for a building, for example, right. You're taking people out of the, out of that harm's way and really standardizing what you're able to do with technology. So we see it as really being on the very entry point of having not only robotics, but technology in general to become much more prevalent in people's lives. >> Yeah. >> I mean, what, you know. 30 years ago, did you ever think that you would have the power of a supercomputer in your pocket to, you know. Which also happens to allow you to talk to people but it is so much more, right? So the power of a cell phone has changed our lives forever. >> A computer that happens to be a phone. You know, it's like, come on. >> Right. >> What's going on with that. >> That's almost secondary at this point. (John laughing) It really is. So, I mean, when you think about that transition from you know, I think we're at the cusp of that right now. We're at the beginning stages of it. And it's really, it's an exciting time to be part of this. An entire industry. >> Before I get your views on integration and scale. Because that's the next level. We're seeing a lot of action and growth. Talk about the use case. You've mentioned a few of them, take people out of harms way. What have you guys seen as use cases within Boston Dynamics customer base and or your partner network around use cases. That either you knew would happen, or ones that might have surprised you? >> Yeah. One of the biggest use cases for us right now is what we're demonstrating here at re:MARS. Which is the ability to walk through a manufacturing plant and collect data off various pieces of equipment. Whether that's pump or a gauge or seeing whether a valve is open or closed. These are all simple mundane tasks that people are, that manufacturers are having difficulty finding people to be able to perform. So the ability for a robot to go over and do that and standardize that process is really valuable. As companies are trying to collect that data in a consistent way. So that's one of the most prevalent use cases that we're seeing right now. And certainly also in cases where, you know, Spot is going into buildings that have been structurally damaged. Or, you know, assessing situations where we don't want people to be in harm's way. >> John: Yeah. >> You know- >> Bomb scares, or any kind of situation with police or, you know, threatening or danger situations. >> Sure. And fire departments as well. I mean, fire departments are becoming a huge, you know, a huge user of the robots themselves. Fire department in New York recently just adopted some of our robots as well. For that purpose, for search and rescue applications. >> Yeah. Go in, go see what's in there. See what's around the corner. It gives a very tactical edge capability for say the firefighter or law enforcement. I see that- I see the military applications must be really insane. >> Sure. From a search and rescue perspective. Absolutely. I mean, Spot helps you put eyes on situations that will allow a human to be operating at a safe distance. So it's really a great value for protecting human life and making sure that people stay out of harm's way. >> Well Eric, I really appreciate you coming on theCUBE and sharing your insight. One other question I'd like to ask if you don't mind is, you know. The one of the things I see next to your booth is the university piece. And then you see the Amazon, you know, material management. I don't know what to call it, but it's pretty impressive. And then I saw some of the demos on the keynotes. Looking at the scale of synthetic data. Just it's mind blowing what's going on in manufacturing. Amazon is pretty state of the art. I'm sure there are a customer of yours already. But they look complex these manufacturing sites. I mean, it looks like a maze. So how do you... I mean, I could see the consequences of something breaking, to be catastrophic. Because it's almost like, it's so integrated. Is this where you guys see success and how do these manufacturers deal with this? What's the... Is it like one big OS? >> Yeah, so the robots, because the robots are able to act independently. They can traverse difficult terrain and collect data on their own. And then, you know, what happens to that data afterwards is really up to the manufacturing. It can be delivered from the cloud and you can, it can be delivered via the edge. You know, edge devices and really that's where some of the exciting work is being done right now. Because that's where data can scale. And that's where robot deployments can scale as well, right? So you've got instead of a single robot. Now you have an operator deploying multiple robots. Monitoring, controlling, and assessing the data from multiple robots throughout a facility. And it really helps to scale that investment. >> All right, final question for you. This is personal question. Okay, I know- Saw your booth over there. And you have a lot of fan base. Spot's got a huge fan base. What are some of the crazy things that these nerd fans do? I mean, everyone get selfies with the Spot. They want to- I jump over the fence. I see, "Don't touch the dog." signs everywhere. The fan base is off the charts. What are the crazy things that people do to get either access to it. There's probably, been probably some theft, probably. Attempts, or selfies. Share some funny stories. >> I'll say this. My team is responsible for fielding a lot of the inbound inquiries that we get. Much of which comes from the entertainment industry. And as you've seen Spot has been featured in some really prominent, you know, entertainment pieces. You know, we were in that Super Bowl ad with Sam Adams. We were on Jimmy Kimmel, you know, during the Super Bowl time period. So the amount of entertainment... >> Value >> Pitches. Or the amount of entertainment value is immeasurable. But the number of pitches that we turn down is staggering. And when you can think about how most companies would probably pull out all the stops to take, you know. To be able to execute half the things that we're just, from a time perspective, from a resource perspective >> Okay, so Spots an A- not always able to do. >> So Spots an A-lister, I get that. Is there a B-lister now? I mean, that sounds like there's a market developing for Spot two. Is there a Spot two? The B player coming in? Understudy? >> So, I mean, Spot is always evolving. I think, you know, the physical- the physical statue that you see of Spot right now, Is where we're going to be in terms of the hardware, but we continue to move the robot forward. It becomes more and more advanced and more and more capable to do more and more things for people. So. >> All right. Well, we'll roll some B roll on this, on theCUBE. Thanks for coming on theCUBE. Really appreciate it. Boston Dynamics here in theCUBE, famous for Spot. And then here, the show packed here in re:MARS featuring, you know, robotics. It's a big feature hall. It's a set piece here in the show floor. And of course theCUBE's covering it. Thanks for watching. More coverage. I'm John Furrier, your host. After the short break. (upbeat music)

(upbeat music) (upbeat music) (upbeat music) >> Welcome back to Las Vegas. Lisa Martin here, with Dave Vellante. We are covering day two of our coverage of Snowflake Summit '22. of Snowflake Summit '22. It's been a cannon of content coming your way, the last couple of days. We love talking with customers, with partners. We've got a partner on the program from ThoughtSpot. We're going to be diving into digital transformation with self-service analytics for the modern data stack. Please welcome Kuntal Vahalia, SVP of Channel and Alliances at ThoughtSpot. Welcome Kuntal. >> Thank you, Lisa. Dave, thank you for having us. >> Dave: Good to see you. >> Talk to the audience a little bit about ThoughtSpot. Give 'em an overview, and then de dive into the partnership with Snowflake. >> Yeah, absolutely. So ThoughtSpot is the, what we call live analytics, for the modern data stack, right? We want to be the experience layer for all the data that's getting modernized and moving into the cloud, right? And then specifically to Snowflake, we, of course, we have seen over the last two days here Snowflake has made tremendous innovations where they've accelerated a customer's journey into the cloud, especially the data cloud. Our job is to go really unlock that data, right? Generate that value, make it consumable at the at the experience level layer, right? So what we want to do here with Snowflake is here with Snowflake is make analytics self service for the end users, for the end users, on top of the Snowflake data cloud, right? And we want to empower everyone to create, consume, and operationalize data driven insights. We think if the end users can gender their own insights through live analytics, we could do have a completely different operating model for a business, right? And I think we can do that in accelerated fashion on, sitting on top of Snowflake data cloud. >> End users? Lines of business? >> It's line of business users, so we directly go to end users. That's one of our differentiation, not just IT, not just IT, but as end users as well, so we could be all things to all enterprise, to all enterprise, across our line of businesses. >> So what kind of impact are you seeing with your customers? You know, ones that are leaning into ThoughtSpot and Snowflake and sort of rethinking their data approach? >> Yeah. I mean the impact could be immense, right? As I said, this is not just about analytics. If we are successful in empowering end users, it completely changes the velocity of the business. We are now driving innovation at every node, at every layer in the organization. Not just IT, not just smaller segments in the organization, we are doing this anywhere, in any pocket, right? So I think the impact could be massive, if we do this right. And I think we are starting to see that, we have a lot of customers here actually, joint customers, Capital One, Canadian Tires, Walmart, they're all joint customers, where we have seen starting to see some of those impacts, where we have data getting modernized, the stack being ready, and then we're coming in at the top as the experience layer, which is driving that new digital operating model. >> Describe the maturity curve when you go, you mentioned some of the the the leaders, I mean, take a Walmart. I mean, they kind of invented the whole, you know, beer and diapers thing, right? So obviously a company with tremendous resources and and and advanced technology. Compare. Compare. So some of those leaders with sort of the other end of the spectrum, when you come into a company and you see, okay, here's, okay, here's, what does that spectrum look like? And and what's the upside for the, I don't want to call 'em laggards, but I'll call 'em laggards. >> Yeah, yeah, absolutely. I mean, this, this, I think we are still early on. I mean, as this is not just a exercise in getting the data ready, this is also an exercise in in change management, because now, as I said, we are going beyond IT. We are going to line of business users as well, so a lot of change management required, and we have seen companies that are actually putting this in front of the frontline workers, empowering frontline workers to consume analytics and to drive self-service via search and AI, and AI, they're on a different curve. They are actually being competitive in the market. That's an advantage for them, right? >> Right. >> So we are seeing a lot of companies, like Walmart, already ahead in that journey with us still early days, right? We got to go, land in one line of business, go from there to other line of business till we go enterprise wide. >> Can you, it sounds like you might be a facilitator of connecting heads of business with the IT and the tech folks at ThoughtSpot. >> Absolutely. I mean, that is the Holy Grail. How do we get IT And line of business work frictionless, where everyone has their roles defined, right? And still get to the outcome where innovation is happening now with IT on the data cloud and then go beyond IT into the broader business? So yeah, I think that's definitely one of the our goals and outcomes of what we do. >> So what are the roles there? So the business obviously wants to do more business. Okay. They put analytics in their hands and it helps them get there. What role does IT play? Making sure that those services are available? Are they a service provider? Is it more of a governance and compliance thing? >> Yeah, I mean, step number one is still to get the data ready and I think IT still owns the key to that kingdom, especially around governance, security, so I think IT still has to get the data stack ready, right? Step number two is for IT to really build a framework for how to consume analytics for how to consume analytics for the end users. Step number three then is, is the rule is, Hey, we don't need IT to now deliver dashboards or KPIs to the business every day that that's how traditional dashboards work. In our world, once IT does step number one and step number two the business can take over and they can now go operate the business on their own using live analytics. >> Creating self-serve >> Absolutely. Self-service analytics using service in AI. >> What have you seen, in terms of from the IT folks perspective, we talked about change management a minute ago, It's very challenging to do, but these days every company has to be a data company. >> Kuntal: Yeah. >> They don't have a choice. >> Yeah. >> What are you seeing from a change management perspective within the IT function across your customers and then be willing to let go in some cases? and then be willing to let go in some cases? >> Actually, >> Actually, what we have seen is, you know, think about the the technical debt that IT is owning over the last few years, it's just increasing, right? IT is looking for ways to A. cut cost, to A. cut cost, B. deliver more B. deliver more with probably the same amount of resources they have, so in some ways they welcome this new operating model, as long as they can keep the governance, they can keep the security, they can keep the framework around how business is run, as long as IT has a say in that, they're more than welcome to invite business, to really drive innovation at the edges through self-service analytics, so what we found is IT is a is a welcome partner, in this journey, especially when they have to get the data ready and modernize the data set for us. >> You guys announcing a partnership with Matillion this week, what? Tell us what that's all about. The one earlier. >> We did. So we did announce a partnership, so I think, as I said, step number one is getting the data ready, and I think we have heard from Frank and the rest of this team this week, even Snowflake is taking a best of breed approach on the data stack, right? So we want the computer So we want the computer and the storage to be ready, but for that, the data pipeline has to be ready, which is where Matillion comes in with the low code, no code approach, so we think between Matillion, Snowflake, and ThoughtSpot, we could be the accelerated best of breed approach for customers to realize value and and be live on the, on the modern data stack. >> Is that your, is that your stack? >> As we said, we, we meet the customers where they are, but we think this is accelerated path. >> What are the advantages of, you know, what are you optimizing on in that stack? in that stack? >> First with Matillion, we have, what we concept, we have this concept of Spot Apps, so this is ThoughtSpot's way to really capture the IP and the templates for customers to move fast, right? That's where we bake in a lot of the industry IP, a lot of functional IP around end sources, and and endpoints, so we have some of those spot apps built with Matillion, built with Matillion, so now customers able to ingest data into the so now customers able to ingest data into the into the cloud faster using Matillion, right? So that's, that's something we worked with, same thing with Snowflake, you know, we are now starting to go verticalize with Snowflake, So we are starting to build a lot of IP around financial services, healthcare and whatnot, which is where I think we are, again, accelerating customer's path on the modern data stack, all the way to the experience layer. >> A as a partner of Snowflake's, what does all the narrative around the data cloud, we've been talking about that for a while, a lot of conversation around the data cloud the last couple of days, where do partners fit into that overall narrative? >> Yeah, I think multiple places, right? First thing, First thing, First thing, every layer of the data cloud still needs innovation, still needs partners, and every partner adds a different set of value. Just like we add value at the, at the top layer, which is the experience layer, But I think, you know, we have channel partners we have a lot of SIs and GSIs here, and GSIs here, especially once we take a best of breed approach, to delivering customer outcomes, SIs are the neutral ground. They're the ones who are going to have the Matillion expertise, and the Snowflake expertise, and thoughts for expertise, all baked into one DNA practice, data analytics practice, so I think at every layer, partners have a role to play and every layer partners have role, have value to add. have value to add. >> What's the engagement process like for customers when you you're talking about the the the the three way partnership Matillion, Matillion, ThoughtSpot, and stuff like, how do customers get involved, what's your go to market look like? >> Right. I mean, obviously, I mean, we, we, we are humble, we know where we are. I mean, we, a little bit smaller than, than Snowflake Snowflake has a head start, so they've been about five years ahead of us, so we are largely targeting customers that are that are Snowflake ready, where there is some semblance of data cloud, where data seems to be organized and ready to go, right? so once we think the customer is at that point in the journey, we have very strong partnership across both, across entire organization, at a product level, at a field engagement level, and our field teams really understand the value the joint value between the two organizations, so we, we start to see Snowflake feel, and ThoughtSpot feel, starting to work together on key accounts, once we think the data is ready, and wherever we need to accelerate the data, that's where we bring in Matillion as well, to ingest more data into, into the data cloud, but that's largely been the engagement model between the three companies. >> How do you see the announcements that they made around applications affecting what you guys are doing and your ecosystem? >> Yeah, I mean, I think that's a validation. I think to us, I think to us, we always said step number one is to modernize the data, move into the cloud. That's step number one, but we still have to unlock the data. Like the data still needs to be consumed, And we always said, Hey, we are that app that could drive the consumption of data, but now with some of the announcement we have seen, I think the validation is there saying, "Hey, yes." There, even Snowflake is ready to move in a more accelerated fashion into the application world where they want to drive consumption, not just with the analytics layer, but with lot of other applications that's out there. >> Yeah. >> What are some of the things that you've heard this week, in the last couple of days, that really validate that really validate the the partnership with Snowflake, from your perspective? >> Yeah. I mean, I think the first thing is, is this concept of modern data stack, which is best of breed. I think we have been thinking about that for a long time, for the last year or so. We have seen this come through at this event here, right? We see Matillion, Snowflake, and then the SIs around it, all coming together, so I think to us, that's the biggest validation that the modern data stack is the right approach, especially best of breed, to drive the right customer outcomes, so to me, that's big. Second is this concept of really accelerating applications on top of the data cloud. I think that's, again a validation of what we've been trying to do over the last few years, which is, the data has modernized, let's now drive consumption and adoption of that data, so I think those are the two big take areas. >> So, so the modern data stack, to get to the modern data stack, you got to do some work. >> Yep. >> But so the, the play is to hold out the carrot, which you just kind of just did, 'cause once you get there, then you can really start to hit the steep part of the S-curve, right? >> That's right. >> What, what are the, what would you say are are the sort of prerequisites that customers need to think about to really jump on that modern data stack curve? >> Um, I think they they got to first have a vision around the outcomes, what outcomes we are driving. I think it's one thing to say, "Hey, we just going to move the data over from from legacy into the cloud." I mean, that's just, that's just migration, that doesn't drive the outcomes. To us, what makes sense is, let's start with the right outcomes around supply chain, around retail, around e-commerce, let's name it, right? I think, it starts there. From there on, let's figure out, what do we need? What's what, what technologies do we need in the stack to enable those outcomes, right? It could be ThoughtSpot at the top, it could be something else at the top, and same thing, it's Matillion, and Snowflake, right? But it really starts with what outcomes we going to drive in what industry and what KPIs are important for our customers. >> What's next for ThoughtSpot and Snowflake? I was just looking at the notes here. Over 250 plus joint customers, you mentioned some Disney+, Capital One, I've seen them around here. What's next for these two powerhouses? >> Well, I think we're just getting started, to be honest. I mean those 250 customers, first, we got to go drive success for them. I mean, we are a 10 year old company with a two year runway because we transferred our business transformed our business to cloud, less than two years ago, so this 250 joint logos are actually all happened in the last two years and that's driven us to be in the, probably in the top five adoption drivers for Snowflake, all in the last two years, So goal number one is to really, let's go drive customer success for these joint logos. Second, let's go expand them, right? Consumption is the key criteria, both for Snowflake, as well as ThoughtSpot. We are very well aligned, our pricing models aligned there, our incentives aligned there, We really want customers to go adopt and consume the stack, and then of course, really, we want to go verticalize ourselves, start speaking the language of the customers, and really just get bigger. I mean, we still got to build a machine around this. >> Lisa: Yep. >> Lisa, this is, this is all still early days for us. >> Early innings. A lot of, but a ton of potential. The, the field is ripe. >> The field is right open. I think in, and we will, I think we are, bottom of the third or bottom of the second, I think you still have a long game to play, right? >> Well good. Most people always use bottom the first. I'm glad to hear it's really bottom of the second or third. That's pretty good. >> Yeah, well, 250 logos are there. >> Lisa: Yeah. >> And it's further along 'cause of the, the I don't want to say it like this, but I'm going to say it anyway. The failure of the big data movement, it pushed us along quite, quite a ways, in terms of thinking, putting data at the core, the technology kind of failed us, you know and the, and the, you know and the, and the, the centralization of the architectures, the centralization of the architectures, it failed us, But then the cloud came along. >> That's right. >> We learned a lot and now, you know, technology's advanced I think people's thinking is advanced and they realize increasingly the importance of data >> And ecosystem is coming. I mean, I think you look around here, this is a secret sauce for the future. >> Dave: Yep. This is what's going to really get us moving faster over the next few innings because now the rest of the ecosystem is coming along. >> Yep. The momentum is here. That flywheel is moving. >> That's right. >> Definitely. Kuntal, thank you very much for joining David and me on the program talking about >> Kuntal: Lisa, Dave, thank you so much for your time. >> what ThoughtSpot's all about, what you're up to, a lot of momentum. We wish you the best of luck as you progress into those later innings. >> Thank you >> For Dave Vellante. I'm Lisa Martin. You're watching theCube. We are live in Las Vegas at Snowflake Summit '22. Dave and I are going to be right back with our next guest, so stick around. (mellow techno music) (mellow techno music) (mellow techno music) (mellow techno music)

>> Instructor: "theCUBE" presents KubeCon and CloudNativeCon Europe 2022, brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain and we're at KubeCon, CloudNativeCon Europe 2022. I'm Keith Townsend, and my co-host, Enrico Signoretti. Enrico's really proud of me. I've called him Enrico instead of Enrique every session. >> Every day. >> Senior IT analyst at GigaOm. We're talking to fantastic builders at KubeCon, CloudNativeCon Europe 2022 about the projects and their efforts. Enrico, up to this point, it's been all about provisioning, insecurity, what conversation have we been missing? >> Well, I mean, I think that we passed the point of having the conversation of deployment, of provisioning. Everybody's very skilled, actually everything is done at day two. They are discovering that, well, there is a security problem. There is an observability problem a and in fact, we are meeting with a lot of people and there are a lot of conversation with people really needing to understand what is happening. I mean, in their cluster work, why it is happening and all the questions that come with it. And the more I talk with people in the show floor here or even in the various sessions is about, we are growing so that our clusters are becoming bigger and bigger, applications are becoming bigger as well. So we need to now understand better what is happening. As it's not only about cost, it's about everything at the end. >> So I think that's a great set up for our guests, Matt Provo, founder and CEO of StormForge and Patrick Brixton? >> Bergstrom. >> Bergstrom. >> Yeah. >> I spelled it right, I didn't say it right, Bergstrom, CTO. We're at KubeCon, CloudNativeCon where projects are discussed, built and StormForge, I've heard the pitch before, so forgive me. And I'm kind of torn. I have service mesh. What do I need more, like what problem is StormForge solving? >> You want to take it? >> Sure, absolutely. So it's interesting because, my background is in the enterprise, right? I was an executive at UnitedHealth Group before that I worked at Best Buy and one of the issues that we always had was, especially as you migrate to the cloud, it seems like the CPU dial or the memory dial is your reliability dial. So it's like, oh, I just turned that all the way to the right and everything's hunky-dory, right? But then we run into the issue like you and I were just talking about, where it gets very very expensive very quickly. And so my first conversations with Matt and the StormForge group, and they were telling me about the product and what we're dealing with. I said, that is the problem statement that I have always struggled with and I wish this existed 10 years ago when I was dealing with EC2 costs, right? And now with Kubernetes, it's the same thing. It's so easy to provision. So realistically what it is, is we take your raw telemetry data and we essentially monitor the performance of your application, and then we can tell you using our machine learning algorithms, the exact configuration that you should be using for your application to achieve the results that you're looking for without over-provisioning. So we reduce your consumption of CPU, of memory and production which ultimately nine times out of 10, actually I would say 10 out of 10, reduces your cost significantly without sacrificing reliability. >> So can your solution also help to optimize the application in the long run? Because, yes, of course-- >> Yep. >> The lowering fluid as you know optimize the deployment. >> Yeah. >> But actually the long-term is optimizing the application. >> Yes. >> Which is the real problem. >> Yep. >> So, we're fine with the former of what you just said, but we exist to do the latter. And so, we're squarely and completely focused at the application layer. As long as you can track or understand the metrics you care about for your application, we can optimize against it. We love that we don't know your application, we don't know what the SLA and SLO requirements are for your app, you do, and so, in our world it's about empowering the developer into the process, not automating them out of it and I think sometimes AI and machine learning sort of gets a bad rap from that standpoint. And so, at this point the company's been around since 2016, kind of from the very early days of Kubernetes, we've always been, squarely focused on Kubernetes, using our core machine learning engine to optimize metrics at the application layer that people care about and need to go after. And the truth of the matter is today and over time, setting a cluster up on Kubernetes has largely been solved. And yet the promise of Kubernetes around portability and flexibility, downstream when you operationalize, the complexity smacks you in the face and that's where StormForge comes in. And so we're a vertical, kind of vertically oriented solution, that's absolutely focused on solving that problem. >> Well, I don't want to play, actually. I want to play the devils advocate here and-- >> You wouldn't be a good analyst if you didn't. >> So the problem is when you talk with clients, users, there are many of them still working with Java, something that is really tough. I mean, all of us loved Java. >> Yeah, absolutely. >> Maybe 20 years ago. Yeah, but not anymore, but still they have developers, they have porting applications, microservices. Yes, but not very optimized, et cetera, cetera, et cetera. So it's becoming tough. So how you can interact with this kind of old hybrid or anyway, not well engineered applications. >> Yeah. >> We do that today. We actually, part of our platform is we offer performance testing in a lower environment and stage and we, like Matt was saying, we can use any metric that you care about and we can work with any configuration for that application. So perfect example is Java, you have to worry about your heap size, your garbage collection tuning and one of the things that really struck me very early on about the StormForge product is because it is true machine learning. You remove the human bias from that. So like a lot of what I did in the past, especially around SRE and performance tuning, we were only as good as our humans were because of what they knew. And so, we kind of got stuck in these paths of making the same configuration adjustments, making the same changes to the application, hoping for different results. But then when you apply machine learning capability to that the machine will recommend things you never would've dreamed of. And you get amazing results out of that. >> So both me and Enrico have been doing this for a long time. Like, I have battled to my last breath the argument when it's a bare metal or a VM, look, I cannot give you any more memory. >> Yeah. >> And the argument going all the way up to the CIO and the CIO basically saying, you know what, Keith you're cheap, my developer resources are expensive, buy bigger box. >> Yeah. >> Yap. >> Buying a bigger box in the cloud to your point is no longer a option because it's just expensive. >> Yeah. >> Talk to me about the carrot or the stick as developers are realizing that they have to be more responsible. Where's the culture change coming from? Is it the shift in responsibility? >> I think the center of the bullseye for us is within those sets of decisions, not in a static way, but in an ongoing way, especially as the development of applications becomes more and more rapid and the management of them. Our charge and our belief wholeheartedly is that you shouldn't have to choose. You should not have to choose between costs or performance. You should not have to choose where your applications live, in a public private or hybrid cloud environment. And so, we want to empower people to be able to sit in the middle of all of that chaos and for those trade offs and those difficult interactions to no longer be a thing. We're at a place now where we've done hundreds of deployments and never once have we met a developer who said, "I'm really excited to get out of bed and come to work every day and manually tune my application." One side, secondly, we've never met, a manager or someone with budget that said, please don't increase the value of my investment that I've made to lift and shift us over to the cloud or to Kubernetes or some combination of both. And so what we're seeing is the converging of these groups, their happy place is the lack of needing to be able to make those trade offs, and that's been exciting for us. >> So, I'm listening and looks like that your solution is right in the middle in application performance, management, observability. >> Yeah. >> And, monitoring. >> Yeah. >> So it's a little bit of all of this. >> Yeah, so we want to be, the intel inside of all of that, we often get lumped into one of those categories, it used to be APM a lot, we sometimes get, are you observability or and we're really not any of those things, in and of themselves, but we instead we've invested in deep integrations and partnerships with a lot of that tooling 'cause in a lot of ways, the tool chain is hardening in a cloud native and in Kubernetes world. And so, integrating in intelligently, staying focused and great at what we solve for, but then seamlessly partnering and not requiring switching for our users who have already invested likely, in a APM or observability. >> So to go a little bit deeper. What does it mean integration? I mean, do you provide data to this, other applications in the environment or are they supporting you in the work that you do. >> Yeah, we're a data consumer for the most part. In fact, one of our big taglines is take your observability and turn it into action ability, right? Like how do you take that, it's one thing to collect all of the data, but then how do you know what to do with it, right? So to Matt's point, we integrate with folks like Datadog, we integrate with Prometheus today. So we want to collect that telemetry data and then do something useful with it for you. >> But also we want Datadog customers, for example, we have a very close partnership with Datadog so that in your existing Datadog dashboard, now you have-- >> Yeah. >> The StormForge capability showing up in the same location. >> Yep. >> And so you don't have to switch out. >> So I was just going to ask, is it a push pull? What is the developer experience when you say you provide developer this resolve ML learnings about performance, how do they receive it? Like, what's the developer experience. >> They can receive it, for a while we were CLI only, like any good developer tool. >> Right. >> And, we have our own UI. And so it is a push in a lot of cases where I can come to one spot, I've got my applications and every time I'm going to release or plan for a release or I have released and I want to pull in observability data from a production standpoint, I can visualize all of that within the StormForge UI and platform, make decisions, we allow you to set your, kind of comfort level of automation that you're okay with. You can be completely set and forget or you can be somewhere along that spectrum and you can say, as long as it's within, these thresholds, go ahead and release the application or go ahead and apply the configuration. But we also allow you to experience the same, a lot of the same functionality right now, in Grafana, in Datadog and a bunch of others that are coming. >> So I've talked to Tim Crawford who talks to a lot of CIOs and he's saying one of the biggest challenges or if not, one of the biggest challenges CIOs are facing are resource constraints. >> Yeah. >> They cannot find the developers to begin with to get this feedback. How are you hoping to address this biggest pain point for CIOs-- >> Yeah.6 >> And developers? >> You should take that one. >> Yeah, absolutely. So like my background, like I said at UnitedHealth Group, right. It's not always just about cost savings. In fact, the way that I look about at some of these tech challenges, especially when we talk about scalability there's kind of three pillars that I consider, right? There's the tech scalability, how am I solving those challenges? There's the financial piece 'cause you can only throw money at a problem for so long and it's the same thing with the human piece. I can only find so many bodies and right now that pool is very small, and so, we are absolutely squarely in that footprint of we enable your team to focus on the things that they matter, not manual tuning like Matt said. And then there are other resource constraints that I think that a lot of folks don't talk about too. Like, you were talking about private cloud for instance and so having a physical data center, I've worked with physical data centers that companies I've worked for have owned where it is literally full, wall to wall. You can't rack any more servers in it, and so their biggest option is, well, I could spend $1.2 billion to build a new one if I wanted to, or if you had a capability to truly optimize your compute to what you needed and free up 30% of your capacity of that data center. So you can deploy additional name spaces into your cluster, like that's a huge opportunity. >> So I have another question. I mean, maybe it doesn't sound very intelligent at this point, but, so is it an ongoing process or is it something that you do at the very beginning, I mean you start deploying this. >> Yeah. >> And maybe as a service. >> Yep. >> Once in a year I say, okay, let's do it again and see if something change it. >> Sure. >> So one spot, one single.. >> Yeah, would you recommend somebody performance test just once a year? Like, so that's my thing is, at previous roles, my role was to do performance test every single release, and that was at a minimum once a week and if your thing did not get faster, you had to have an executive exception to get it into production and that's the space that we want to live in as well as part of your CICD process, like this should be continuous verification, every time you deploy, we want to make sure that we're recommending the perfect configuration for your application in the name space that you're deploying into. >> And I would be as bold as to say that we believe that we can be a part of adding, actually adding a step in the CICD process that's connected to optimization and that no application should be released, monitored, and sort of analyzed on an ongoing basis without optimization being a part of that. And again, not just from a cost perspective, but for cost and performance. >> Almost a couple of hundred vendors on this floor. You mentioned some of the big ones Datadog, et cetera, but what happens when one of the up and comings out of nowhere, completely new data structure, some imaginative way to click to telemetry data. >> Yeah. >> How do, how do you react to that? >> Yeah, to us it's zeros and ones. >> Yeah. >> And, we really are data agnostic from the standpoint of, we're fortunate enough from the design of our algorithm standpoint, it doesn't get caught up on data structure issues, as long as you can capture it and make it available through one of a series of inputs, one would be load or performance tests, could be telemetry, could be observability, if we have access to it. Honestly, the messier the better from time to time from a machine learning standpoint, it's pretty powerful to see. We've never had a deployment where we saved less than 30%, while also improving performance by at least 10%. But the typical results for us are 40 to 60% savings and 30 to 40% improvement in performance. >> And what happens if the application is, I mean, yes Kubernetes is the best thing of the world but sometimes we have to, external data sources or, we have to connect with external services anyway. >> Yeah. >> So, can you provide an indication also on this particular application, like, where the problem could be? >> Yeah. >> Yeah, and that's absolutely one of the things that we look at too, 'cause it's, especially when you talk about resource consumption it's never a flat line, right? Like depending on your application, depending on the workloads that you're running it varies from sometimes minute to minute, day to day, or it could be week to week even. And so, especially with some of the products that we have coming out with what we want to do, integrating heavily with the HPA and being able to handle some of those bumps and not necessarily bumps, but bursts and being able to do it in a way that's intelligent so that we can make sure that, like I said, it's the perfect configuration for the application regardless of the time of day that you're operating in or what your traffic patterns look like, or, what your disc looks like, right. Like 'cause with our low environment testing, any metric you throw at us, we can optimize for. >> So Matt and Patrick, thank you for stopping by. >> Yeah. >> Yes. >> We can go all day because day two is I think the biggest challenge right now, not just in Kubernetes but application re-platforming and transformation, very, very difficult. Most CTOs and EASs that I talked to, this is the challenge space. From Valencia, Spain, I'm Keith Townsend, along with my host Enrico Signoretti and you're watching "theCube" the leader in high-tech coverage. (whimsical music)

>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to Melissa Spain. And we're at cuon cloud native con Europe, 2022. I'm Keith Townsend. And my co-host en Rico senior Etti en Rico's really proud of me. I've called him en Rico and said IK, every session, senior it analyst giga, O we're talking to fantastic builders at Cuban cloud native con about the projects and the efforts en Rico up to this point, it's been all about provisioning insecurity. What, what conversation have we been missing? >>Well, I mean, I, I think, I think that, uh, uh, we passed the point of having the conversation of deployment of provisioning. You know, everybody's very skilled, actually everything is done at day two. They are discovering that, well, there is a security problem. There is an observability problem. And in fact, we are meeting with a lot of people and there are a lot of conversation with people really needing to understand what is happening. I mean, in their classroom, what, why it is happening and all the, the questions that come with it. I mean, and, uh, the more I talk with, uh, people in the, in the show floor here, or even in the, you know, in the various sessions is about, you know, we are growing, the, our clusters are becoming bigger and bigger. Uh, applications are becoming, you know, bigger as well. So we need to know, understand better what is happening. It's not only, you know, about cost it's about everything at the >>End. So I think that's a great set up for our guests, max, Provo, founder, and CEO of storm for forge and Patrick Britton, Bergstrom, Brookstone. Yeah, I spelled it right. I didn't say it right. Berg storm CTO. We're at Q con cloud native con we're projects are discussed, built and storm forge. I I've heard the pitch before, so forgive me. And I'm, I'm, I'm, I'm, I'm, I'm kind of torn. I have service mesh. What do I need more like, what problem is storm for solving? >>You wanna take it? >>Sure, absolutely. So it it's interesting because, uh, my background is in the enterprise, right? I was an executive at United health group. Um, before that I worked at best buy. Um, and one of the issues that we always had was, especially as you migrate to the cloud, it seems like the CPU dial or the memory dial is your reliability dial. So it's like, oh, I just turned that all the way to the right and everything's hunky Dory. Right. Uh, but then we run into the issue like you and I were just talking about where it gets very, very expensive, very quickly. Uh, and so my first conversations with Matt and the storm forge group, and they were telling me about the product and, and what we're dealing with. I said, that is the problem statement that I have always struggled with. And I wish this existed 10 years ago when I was dealing with EC two costs, right? And now with Kubernetes, it's the same thing. It's so easy to provision. So realistically, what it is is we take your raw telemetry data and we essentially monitor the performance of your application. And then we can tell you using our machine learning algorithms, the exact configuration that you should be using for your application to achieve the results that you're looking for without over provisioning. So we reduce your consumption of CPU of memory and production, which ultimately nine times outta 10, actually I would say 10 out of 10 reduces your cost significantly without sacrificing reliability. >>So can your solution also help to optimize the application in the long run? Because yes, of course, yep. You know, the lowing fluid is, you know, optimize the deployment. Yeah. But actually the long term is optimizing the application. Yes. Which is the real problem. >>Yep. So we actually, um, we're fine with the, the former of what you just said, but we exist to do the latter. And so we're squarely and completely focused at the application layer. Um, we are, uh, as long as you can track or understand the metrics you care about for your application, uh, we can optimize against it. Um, we love that we don't know your application. We don't know what the SLA and SLO requirements are for your app. You do. And so in, in our world, it's about empowering the developer into the process, not automating them out of it. And I think sometimes AI and machine learning sort of gets a bad wrap from that standpoint. And so, uh, we've at this point, the company's been around, you know, since 2016, uh, kind of from the very early days of Kubernetes, we've always been, you know, squarely focused on Kubernetes using our core machine learning, uh, engine to optimize metrics at the application layer, uh, that people care about and, and need to need to go after. And the truth of the matter is today. And over time, you know, setting a cluster up on Kubernetes has largely been solved. Um, and yet the promise of, of Kubernetes around portability and flexibility, uh, downstream when you operationalize the complexity, smacks you in the face. And, uh, and that's where, where storm forge comes in. And so we're a vertical, you know, kind of vertically oriented solution. Um, that's, that's absolutely focused on solving that problem. >>Well, I don't want to play, actually. I want to play the, uh, devils advocate here and, you know, >>You wouldn't be a good analyst if you didn't. >>So the, the problem is when you talk with clients, users, they, there are many of them still working with Java with, you know, something that is really tough. Mm-hmm <affirmative>, I mean, we loved all of us loved Java. Yeah, absolutely. Maybe 20 years ago. Yeah. But not anymore, but still they have developers. They are porting applications, microservices. Yes. But not very optimized, etcetera. C cetera. So it's becoming tough. So how you can interact with these kind of yeah. Old hybrid or anyway, not well in generic applications. >>Yeah. We, we do that today. We actually, part of our platform is we offer performance testing in a lower environment and stage. And we like Matt was saying, we can use any metric that you care about and we can work with any configuration for that application. So the perfect example is Java, you know, you have to worry about your heap size, your garbage collection tuning. Um, and one of the things that really struck, struck me very early on about the storm forage product is because it is true machine learning. You remove the human bias from that. So like a lot of what I did in the past, especially around SRE and, and performance tuning, we were only as good as our humans were because of what they knew. And so we were, we kind of got stuck in these paths of making the same configuration adjustments, making the same changes to the application, hoping for different results. But then when you apply machine learning capability to that, the machine will recommend things you never would've dreamed of. And you get amazing results out of >>That. So both me and an Rico have been doing this for a long time. Like I have battled to my last breath, the, the argument when it's a bare metal or a VM. Yeah. Look, I cannot give you any more memory. Yeah. And the, the argument going all the way up to the CIO and the CIO basically saying, you know what, Keith you're cheap, my developer resources expensive, my bigger box. Yep. Uh, buying a bigger box in the cloud to your point is no longer a option because it's just expensive. Talk to me about the carrot or the stick as developers are realizing that they have to be more responsible. Where's the culture change coming from? So is it, that is that if it, is it the shift in responsibility? >>I think the center of the bullseye for us is within those sets of decisions, not in a static way, but in an ongoing way, especially, um, especially as the development of applications becomes more and more rapid. And the management of them, our, our charge and our belief wholeheartedly is that you shouldn't have to choose, you should not have to choose between costs or performance. You should not have to choose where your, you know, your applications live, uh, in a public private or, or hybrid cloud environment. And so we want to empower people to be able to sit in the middle of all of that chaos and for those trade-offs and those difficult interactions to no, no longer be a thing. You know, we're at, we're at a place now where we've done, you know, hundreds of deployments and never once have we met a developer who said, I'm really excited to get outta bed and come to work every day and manually tune my application. <laugh> One side, secondly, we've never met, uh, you know, uh, a manager or someone with budget that said, uh, please don't, you know, increase the value of my investment that I've made to lift and shift us over mm-hmm <affirmative>, you know, to the cloud or to Kubernetes or, or some combination of both. And so what we're seeing is the converging of these groups, um, at, you know, their happy place is the lack of needing to be able to, uh, make those trade offs. And that's been exciting for us. So, >>You know, I'm listening and looks like that your solution is right in the middle in application per performance management, observability. Yeah. And, uh, and monitoring. So it's a little bit of all of this. >>So we, we, we, we want to be, you know, the Intel inside of all of that, mm-hmm, <affirmative>, we don't, you know, we often get lumped into one of those categories. It used to be APM a lot. We sometimes get a, are you observability or, and we're really not any of those things in and of themselves, but we, instead of invested in deep integrations and partnerships with a lot of those, uh, with a lot of that tooling, cuz in a lot of ways, the, the tool chain is hardening, uh, in a cloud native and, and Kubernetes world. And so, you know, integrating in intelligently staying focused and great at what we solve for, but then seamlessly partnering and not requiring switching for, for our users who have already invested likely in a APM or observability. >>So to go a little bit deeper. Sure. What does it mean integration? I mean, do you provide data to this, you know, other applications in, in the environment or are they supporting you in the work that you >>Yeah, we're, we're a data consumer for the most part. Um, in fact, one of our big taglines is take your observability and turn it into actionability, right? Like how do you take the it's one thing to collect all of the data, but then how do you know what to do with it? Right. So to Matt's point, um, we integrate with folks like Datadog. Um, we integrate with Prometheus today. So we want to collect that telemetry data and then do something useful with it for you. >>But, but also we want Datadog customers. For example, we have a very close partnership with, with Datadog, so that in your existing data dog dashboard, now you have yeah. This, the storm for capability showing up in the same location. Yep. And so you don't have to switch out. >>So I was just gonna ask, is it a push pull? What is the developer experience? When you say you provide developer, this resolve ML, uh, learnings about performance mm-hmm <affirmative> how do they receive it? Like what, yeah, what's the, what's the, what's the developer experience >>They can receive it. So we have our own, we used to for a while we were CLI only like any good developer tool. Right. Uh, and you know, we have our own UI. And so it is a push in that, in, in a lot of cases where I can come to one spot, um, I've got my applications and every time I'm going to release or plan for a release or I have released, and I want to take, pull in, uh, observability data from a production standpoint, I can visualize all of that within the storm for UI and platform, make decisions. We allow you to, to set your, you know, kind of comfort level of automation that you're, you're okay with. You can be completely set and forget, or you can be somewhere along that spectrum. And you can say, as long as it's within, you know, these thresholds, go ahead and release the application or go ahead and apply the configuration. Um, but we also allow you to experience, uh, the same, a lot of the same functionality right now, you know, in Grafana in Datadog, uh, and a bunch of others that are coming. >>So I've talked to Tim Crawford who talks to a lot of CIOs and he's saying one of the biggest challenges, or if not, one of the biggest challenges CIOs are facing are resource constraints. Yeah. They cannot find the developers to begin with to get this feedback. How are you hoping to address this biggest pain point for CIOs? Yeah. >>Development? >>Just take that one. Yeah, absolutely. That's um, so like my background, like I said, at United health group, right. It's not always just about cost savings. In fact, um, the way that I look about at some of these tech challenges, especially when we talk about scalability, there's kind of three pillars that I consider, right? There's the tech scalability, how am I solving those challenges? There's the financial piece, cuz you can only throw money at a problem for so long. And it's the same thing with the human piece. I can only find so many bodies and right now that pool is very small. And so we are absolutely squarely in that footprint of, we enable your team to focus on the things that they matter, not manual tuning like Matt said. And then there are other resource constraints that I think that a lot of folks don't talk about too. >>Like we were, you were talking about private cloud for instance. And so having a physical data center, um, I've worked with physical data centers that companies I've worked for have owned where it is literally full wall to wall. You can't rack any more servers in it. And so their biggest option is, well, I could spend 1.2 billion to build a new one if I wanted to. Or if you had a capability to truly optimize your compute to what you needed and free up 30% of your capacity of that data center. So you can deploy additional name spaces into your cluster. Like that's a huge opportunity. >>So either out of question, I mean, may, maybe it, it doesn't sound very intelligent at this point, but so is it an ongoing process or is it something that you do at the very beginning mean you start deploying this. Yeah. And maybe as a service. Yep. Once in a year I say, okay, let's do it again and see if something changes. Sure. So one spot 1, 1, 1 single, you know? >>Yeah. Um, would you recommend somebody performance tests just once a year? >>Like, so that's my thing is, uh, previous at previous roles I had, uh, my role was you performance test, every single release. And that was at a minimum once a week. And if your thing did not get faster, you had to have an executive exception to get it into production. And that's the space that we wanna live in as well as part of your C I C D process. Like this should be continuous verification every time you deploy, we wanna make sure that we're recommending the perfect configuration for your application in the name space that you're deploying >>Into. And I would be as bold as to say that we believe that we can be a part of adding, actually adding a step in the C I C D process that's connected to optimization and that no application should be released monitored and sort of, uh, analyzed on an ongoing basis without optimization being a part of that. And again, not just from a cost perspective, yeah. Cost end performance, >>Almost a couple of hundred vendors on this floor. You know, you mentioned some of the big ones, data, dog, et cetera. But what happens when one of the up and comings out of nowhere, completely new data structure, some imaginable way to click to elementry data. Yeah. How do, how do you react to that? >>Yeah. To us it's zeros and ones. Yeah. Uh, and you know, we're, we're, we're really, we really are data agnostic from the standpoint of, um, we're not, we we're fortunate enough to, from the design of our algorithm standpoint, it doesn't get caught up on data structure issues. Um, you know, as long as you can capture it and make it available, uh, through, you know, one of a series of inputs, what one, one would be load or performance tests, uh, could be telemetry, could be observability if we have access to it. Um, honestly the messier, the, the better from time to time, uh, from a machine learning standpoint, um, it, it, it's pretty powerful to see we've, we've never had a deployment where we, uh, where we saved less than 30% while also improving performance by at least 10%. But the typical results for us are 40 to 60% savings and, you know, 30 to 40% improvement in performance. >>And what happens if the application is, I, I mean, yes, Kubernetes is the best thing of the world, but sometimes we have to, you know, external data sources or, or, you know, we have to connect with external services anyway. Mm-hmm <affirmative> yeah. So can you, you know, uh, can you provide an indication also on, on, on this particular application, like, you know, where the problem could >>Be? Yeah, yeah. And that, that's absolutely one of the things that we look at too, cuz it's um, especially when you talk about resource consumption, it's never a flat line, right? Like depending on your application, depending on the workloads that you're running, um, it varies from sometimes minute to minute, day to day, or it could be week to week even. Um, and so especially with some of the products that we have coming out with what we want to do, you know, partnering with, uh, you know, integrating heavily with the HPA and being able to handle some of those bumps and not necessarily bumps, but bursts and being able to do it in a way that's intelligent so that we can make sure that, like I said, it's the perfect configuration for the application regardless of the time of day that you're operating in or what your traffic patterns look like. Um, or you know, what your disc looks like, right? Like cuz with our, our low environment testing, any metric you throw at us, we can, we can optimize for. >>So Madden Patrick, thank you for stopping by. Yeah. Yes. We can go all day. Because day two is I think the biggest challenge right now. Yeah. Not just in Kubernetes, but application replatforming and re and transformation. Very, very difficult. Most CTOs and S that I talked to, this is the challenge space from Valencia Spain. I'm Keith Townsend, along with my host en Rico senior. And you're watching the queue, the leader in high tech coverage.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Cybersecurity stocks have been sending mixed signals as of late, mostly negative like much of tech, but some such as Palo Alto Networks, despite a tough go of it recently have held up better than most tech names. Others like CrowdStrike, had been out performing Broader Tech in March, but then flipped in May. Okta's performance was pretty much tracking along with CrowdStrike for most of the past several months, a little bit below, but then the Okta hack changed the trajectory of that name. Zscaler has crossed the critical billion dollar ARR revenue milestone, and now sees a path to five billion dollars in revenue, but the company stock fell sharply after its last earnings report and has been on a down trend since last November. Meanwhile, CyberArk's recent beat and raise, was encouraging and the stock acted well after its last report. Security remains the number one initiative priority amongst IT organizations and the spending momentum for many high flying cyber names remain strong. So what gives in cyber security? Hello, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we focus on security and will update you on the latest data from ETR to try to make sense out of the market and read into what this all means in both the near and long term, for some of our favorite names in cyber. First, the news. There's always something happening in security news cycles. The big recent news is new President Rodrigo Chavez declared a national emergency in Costa Rica due to the preponderance of Russian cyber attacks on the country's critical infrastructure. Such measures are normally reserved for natural disasters like earthquakes, but this move speaks to the nature of today's cyber threats. Of no surprise is modern superpower warfare even for a depleted power like Russia almost certainly involves cyber warfare as we continue to see in Ukraine. Privately held Arctic Wolf Networks hired Dustin Williams as its new CFO. Williams has taken three companies to IPO, including Nutanix in 2016, a very successful IPO for that company. Whether AWN chooses to pull the trigger this year or will wait until markets are less choppy or obviously remains to be seen. But it's a pretty clear sign the company is headed to IPO at some point. Now, big point of discussion this week at Red Hat Summit in Boston and the prior week at Dell technologies world was security. In the case of Red Hat, securing the digital supply chain was the main theme. And from Dell building, many security features into its storage arrays and cyber resilience services into its as a service offering called Apex. And we're seeing a trend where buyers want to reduce the number of bespoke tools they use if they, in fact can. Here's IDC's Jim Mercer, sharing data from a recent survey they conducted on the topic. Play the clip. >> Interestingly, we did a survey, I think around last August or something. And one of the questions was around where do you want your security, right? Where do you want to get your DevSecOps security from? Do you want to get it from individual vendors, right? Or do you want to get it from like your platforms that you're using and deploying changes in Kubernetes? >> Great question. What did they say? >> The majority of them, they're hoping they can get it built into the platform. That's really what they want-- >> Now, whether that's actually achievable is debatable because you have so much innovation and investment going on from the likes of startups and for instance, lace work or sneak and security companies that you see even trying to build platforms, you've got CrowdStrike, Okta, Zscaler and many others, trying to build security platforms and put it all under their umbrella. Now the last point will hit here is there was a lot of buzz in the news about Okta. The reaction to what was a relatively benign hack was pretty severe and probably overblown, but Okta's stock is paying the price of what is generally considered a blown communications plan versus a technical failure. Remember, identity is not an easy thing to rip and replace and Okta remains a best-of-breed player and leader in the space. So we're going to look at some ETR data later in this segment to try and make sense of the recent action in the market and certain names. Speaking of which let's take a look at how some of the names in cybersecurity have fared relative to some of the indices and relative indicators that we like to look at. Here's a Google finance comparison for a number of stocks and names in the bottom there you can see we plot the hack ETF which tracks security stocks. This is a year to date view. And so we don't show it here but the tech heavy NASDAQ is off around 26% year to date whereas the cyber ETF that we're showing is down 18%, okay. So cyber holding up a little bit better than broader tech as we've reported earlier, was actually much better and still seems to be a gap there, but the data are mixed. You can see Okta is way off relative to its peers. That's a combination of the breach that we talked about but also the run up in the stock since COVID. CrowdStrike was actually faring better but broke this month, we'll see how it's upcoming earnings announcements are received when it announces on June 2nd after the close. Palo Alto in the light blue has done better than most and until recently was holding up quite well. And of course, Sailpoint is another identity specialist, it is kind of off the charts here because it's going private with the acquisition by Thoma Bravo at nearly seven billion dollars. So you see some mixed signals in cyber these past several months and weeks. And so we're trying to understand what that all means. So let's take a look at the survey data and see how spending momentum is holding up. As we've reported IT spending forecast, at the macro level, they've come off their 8% highs from the end of the year, the ETRS December survey, but robust tech spending is still there. It's expected at nearly seven percent and this is amongst 1200 ETR respondents. Here's a picture from the ETR survey of the cybersecurity landscape. That y-axis that's net score or a measure of spending momentum and that horizontal access is overlap. We used to talk about it as a market share which is a measure of pervasiveness in the data set. That dotted red line at 40% indicates an elevated spending momentum level on the vertical axis and we filter the names and limited to only those with a hundred or more responses in the ETR survey. Then the pictures still pretty crowded as you can see. You got lots of companies above the red dotted line, including Microsoft which is up into the right, they're so far off the chart, it's just amazing. But also Palo Alto and Okta, Auth0, which of course is now owned by Okta, Zscaler, CyberArk is making moves. Sailpoint and Cloudflare, they're all above that magic 40% line. Now, you look at Cisco, it shows a very large presence in the horizontal axis in the data set. And it's got pretty respectable momentum and you see Splunk doing okay, no before and tenable just below that 40% line and a lot of names in the very respectable 20% zone. And we've included some legacy names just for context that fall below the zero percent line with a negative net score. And that means a larger proportion, that negative net score means a larger proportion of their customers in the survey are spending less than those that are spending more. Now, typically for these legacy names you're going to have a huge proportion of customers who have flat spending that kind of fat middle and that's why they sort of don't have that highly elevated score, but they're still viable as they get the recurring revenue each year. But the bottom line is that spending remains robust for some of the top names that we've talked about earlier despite their rocky stock performance. Now, let's filter this data a bit more to make it a little bit easier to read. So to do that, we take out Microsoft because they're just so dominant and we cherry pick some names to make the data more consumable and scannable. The other data point we've added is Okta's net score breakdown, the multicolored rows there, that row in the bottom right. Net score, it measures the percent of customers that are adding the platform new, that's the lime green, at 18% for Okta. The forest green is at 42%. That's the percent of customers in the survey that are spending six percent or more. The gray is flat spending. That's 32% for Okta, this past survey. The pink is customers that are spending less, that's three percent. They're spending six percent or worse in the survey, so only three percent for Okta. And the bright red at three percent is decommissioning the platform. You subtract the reds from the greens and you get a net score, well, into the 50s for Okta and you can see. We highlight Okta here because it's a name that we've been following for quite some time and customers have given us really solid feedback on the technology and up until the hack, they're affinity to Okta, but that seems to be continuing. We'll talk more about that. This recent breach to Okta has caused us to take a closer look. And you may recall, we reported with our ETR colleague, Eric Bradley. The breach was announced right in the middle of ETR collecting data in the last survey. And while we did see a noticeable downtick right after the announcement, the exposure of the hack and Okta's net score just after the breach was disclosed, you can see the combination of Okta and Auth0 remains very strong. I asked Eric Bradley this morning what he thought about Okta, and he pointed out that you can't evaluate this company on its price to earnings ratio. But it's forward sales multiple is now below 7X. And while attractive, these high flyers at some point, Eric says, they got to start making a profit. So you going to hold that thought, we'll come back to that. Now, another cut of the ETR data to look at our four star security names here. A while back we developed a methodology to try and cut through the noise of the crowded security sector using the ETR data to evaluate two key metrics; net score and shared N. Net score again is, spending momentum, the latter is an indicator of presence in the data set which is a proxy for market presence. Okay, we assigned those companies that cracked the top 10 in both net score and shared N, we give them four stars, okay, if they make the top 10. This chart here shows the April survey data for those companies with an N that's greater than, equal to a hundred responses. So again, we're filtering on those with a hundred or more responses. The table on the left that you see there, that's sorted by net score, okay. So we're sorting by spending momentum. And then the one on the right is sorted by shared N, so their presence in the data set. Seven companies hit the top 10 for both categories; Palo Alto Network, Splunk, CrowdStrike Okta, Proofpoint, Fortinet and Zscaler. Now, remember, take a look, Okta excludes Auth0, in this little methodology that we came up with. Auth0 didn't make the cuts but it hits the top 10 for net score. So if you add in Auth0's 112 N there that you see on the right. You add that into Okta, we put Okta in the number two spot in the survey on the right most table with the shared N of 354. Only Cisco has a higher presence in the data set. And you can see Cisco in the left lands just below that red dotted line. That's the top 10 in security. So if we were to combine Okta and Auth0 as one, Cisco would make the cut and earn four stars. Now, some other notables are CyberArk, which is just below the red line on the right most chart with an impressive 177 shared N. Again, if you combine Auth0 and Okta, CyberArk makes the four star grade because it's in the top 10 for net score on the left. And Sailpoint is another notable with a net score above 50% and it's got a shared N of 122, which is respectable. So despite the market's choppy waters, we're seeing some positive signs in the survey data for some of the more prominent names that we've been following for the last couple of years. So what does this mean for the markets going forward? As always, when we see these confusing signs we like to reach out to the network and one of the sharpest traders out there is Chip Simonton. We've quoted him before and we like to share some of his insights. And so we're going to highlight some of that here. So technically, almost every good tech stock is oversold. And as such, he suggested we might see a bounce here. We certainly are seeing that on this Friday, the 13th. But the right call tactically has been to sell into the rally these past several months, so we'll see what happens on Monday. The key issue with the name like Okta and some other momentum names like CrowdStrike and Zscaler is that when money comes back into tech, it's likely going to go to the FAANG stocks, the Facebook, Apple, Amazon, Netflix, Google, and of course, you put Microsoft in there as well. And we'll see about Amazon, by the way, it's kind of out of favor right now, as everyone's focused on the retail side of the business meanwhile it's cloud business is booming and that's where all the profit is. We think that should be the real focus for Amazon. But the point is, for these momentum names in cybersecurity that don't make money, they face real headwinds, as growth is slowing overall and interest rates rise, that makes the net present value of these investments much less attractive. We've talked about that before. But longer term, we agree with Chip Simonton that these are excellent companies and they will weather the storm and we think they're going to lead their respective markets. And in cyber, we would expect continued M&A activity, which could act as a booster shot in the arms of these names. Now in 2019, we saw the ETR data, it pointed to CrowdStrike, Zscaler, Okta and others in the security space. Some of those names that really looked to us like they were moving forward and the pandemic just created a surge in these names and admittedly they got out over their skis. But the data suggests that these leading companies have continued momentum and the potential for stay in power. Unlike the SolarWinds hack, it seems at this point anyway that Okta will recover in the market. For the reasons that we cited, investors, they might stay away for some time but longer term, there's a shift in CSO security strategies that appear to be permanent. They're really valuing cloud-based modern platforms, these platforms will likely continue to gain share and carry their momentum forward. Okay, that's it for now, thanks to Stephanie Chan, who helps with the background research and with social, Kristen Martin and Cheryl Knight help get the word out and do some great work as well. Alex Morrison is on production and handles all of our podcast. Alex, thank you. And Rob Hof is our Editor in Chief at SiliconANGLE. Remember, all these episodes, they're available as podcast, you can pop in the headphones and listen, just search "Breaking Analysis Podcast." I publish each week on wikibon.com and SiliconANGLE.com. Don't forget to check out etr.ai, best in the business for real customer data. It's an awesome platform. You can reach me at dave.vellante@siliconangle.com or @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for the CUBEinsights powered by ETR. Thanks for watching. And we'll see you next time. (bright upbeat music)