>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen brought to you by bread hat. >> Well, good afternoon. Where you might be watching us here on the Cube. We are live in Boston. Is we wrap up our coverage headed toward the homestretch? You might say of Red had Summit twenty nineteen. Want was to Mittleman. I'm John Walls. And thank you for joining us here. We're now joined by Ah, Louise, right. Bower, who was the vice president and chief technical strategists and head of innovation lab at Dinah Trees. And always good to see you today. Thanks for being with us. Hello. Thanks for having me s O software intelligence that that's your your primary focus. You've got headquarters here in the Boston area back in Austria. Tell a little bit about it. You would, Dina Trace. And I guess first off, what this news this week has met to you in terms of the release is and then maybe what you're doing in general. You know what Dina Trace is all about? >> Yes. Oh, that phrase has been around for, like quite a time. Started out as an a P M. Company. like fourteen years ago have been reinventing ourselves over and over again on DH. So we move from the traditional monitoring approach. So the innovation we had in the very beginning when we launched the first product was really would be practical, pure passer. The ability trace and went that way a lot about facing racing, like becoming super cool for micro services. So it would be like the first teacher we could be burying, doing, tracing before it was cool, like forty, fifty years ago. And then I was were involving the product more, more Skilling into bigger and bigger environments. So what's bigger and bigger mean? I remember in the beginning when we were working on environments who we're talking about, like one hundred host has a big environment like five hundred told that that's a big environment today, we say, for even one hundred thousand toast. Okay, it's a big environment, but they can't get even bigger then. The massive change was really for us five years ago, where way implemented our entire product offering, built the new Dina trays, Mr Focus, that we realize that okay, it's data and between people date and having them analyzed data is nice, but it's only getting you so far. So the more complex the replication get, more data you get to analyze. And it's just more exponentially scaling how many people you would need to deal with this. And that's why five years ago, we started to incorporate a I into our new court platform, then for automatic problem analysis. That's also where we're not just BPM. That's just what we call like the Dogg Tools data on glass tools to show a lot of data. Do some analysis on top of it. But it don't help you, too, really resolve a problem. So we used build in the eye, and that automatic would cause analysis again. Next teacher doing Aye, aye ops, affordable school like five years ago. Andi. The latest evolution. We also so again, and not a change in the way people are using monitoring tools. Um, we've invested a lot into building out in AP eyes don't see monitoring tools like be the Martin still here and the application over there, but having them monitoring who being highly integrated into the fabric fire eyes. So we have, As of today, eighty percent of our customers are using the product also via reprise, but tying them into operational automation. What we heard even today in the keynote here about a ABS and Howie iop starts to control and manage that form. More is becoming the intelligence or the back plane behind a modern native stack. >> So we have Chris right on. Who was in the keynote this morning? Came on our program this morning, too, when we talked about just the rippling effects of distributed architectures. I look at my applications there, you know, going to micro service architectures. You look at where's customers data? Well, lots of stuff all over the clouds and sass, and that has a ripple. Effect it to your space. You know, I hear observe, ability monitoring, you know, hack even bring up, like, you know, the civilised world. It becomes a whole separate meeting. So Donna Trace has been going through a transformation. You know, give >> us a >> point check ins to you know, where your customers are, how you're helping them move through this modernization and, you know, move to distributed architectures where that fits in >> so that their customers we focus on mostly are like Fortune five hundred customers who we work with. And obviously they have everything that exists on the planet. When we talk about self for like even from the mainframe to cloud native to serve less, as you mentioned here. And they were in this transition process right now, like modernizing their applications, which, as a necessity, we all want to move fast. There we want therefore flexible architects is we want to build more enough innovative products but at the same time to realize that this is also a message business risk behind following this approach. Think about you in the role of the CEO and say where we're going to modernize our architecture. We're going to rebuild everything we platform and so forth. You can if you succeed. Everybody would say you had. Yes, you did what you had to do. I mean, sorry if you failed, you failed. It's s so for them, it's a It's a big risk to move down that route and retired to take that risk out of the process as much as possible. Really Starting, obviously was monitoring their traditional sex, as they have to today, but really supporting that along that entire journey to a cloud native architecture er, starting with what we referred to as our support for monoliths to micro service architecture's. So Theodore is basically you don't want to rip apart the replication and figure out how it's going to work in my purse services world. But we have to technology that's called smart scape smart. Skip Moelis bills a real time, all of your entire data center and old applications running into it. And it was virtually that sect. You're marvelous, you came. How would they look like in a microt services architecture without catching any codes and then making it work? So once you've done this once, you've decided to move there the next step? Obviously, yes, you could have rebuilt that application. Usually we see applications with micro services architectures being significantly Mohr complex or more distributed by the sign that a traditional that you might have Web server application, Teo Database Server. Now you might be talking about maybe two hundred micro services or more so twenty times ranges. Writer on this under under lower bound here, which means that your traditional operational approach up okay, it's either the database of observer. The application server doesn't work anymore. on top of this. You did all of this to deploy fast. Like for like, bi weekly releases, even maybe daily off, like a smaller granularity. So you were reading a lot of entropy to that system and you have to analyze way more data. Did he ever had to do before? And this is where we kind of getting to the level where theoretically humans could do it. But it would just take us too long where the Holy I ops capability come in where we let let the machines that a monitoring tto take care of it at that level. So we helping them to operation US thieves processes and then really supporting them along the whole journey, where every customer we talked like this vision. But we're also here today in the keynote of an autonomous cloud and with carbonated, we already made a great step in this direction, looking at the interest, actually, like today say, I need five replicas off this container. I don't know, given that it's does it open shift and specifically here, it's going to happen. But if we move to the application layer is a lot, that has to be done and it has to make it easier for people to do. And that's where we tied into the entire customers. Ecosystem toe, automate like their cloud environment and have actually built a practice around which we call autonomous cloud management that we have been working with with customers on to enable them to achieve this over time. But it's going to be a lot maturity there. >> Yes, I mean, so what it talked about that you know, a CIA autonomous cloud management. What exactly you know, is that and how are you bringing that to your customer >> base? Autonomous Cloud Management resulted out off two different areas. The first one was when we were implement re implementing our platform. What I mentioned before, one step for us was to move to the SAS platform, and we looked at all the operation practices that were around back then, you know, we don't want to tell the doc I really don't want to do it. Like having people twenty four seven look at dashboards, then goingto a wicky, then reading a description of how to fix the problem. If you're the engineer, that why why do we do this this way? Must make any sense. So we developed our own practice, which we referred to as no wops. I know it doesn't mean that you're not doing operations. That would be pretty crazy, but not doing this traditional Naga type of operation, sitting there staring at a screen twenty four seven and then mentally executing any operation. So we had our own practice that we've built around it and, quite frankly, which has spilled it because we needed it for ourselves, and then we kept talking to customers and partisan, he says. Really cool what you did there like, Oh, how did you do this? What's like yourself? Respect behind this and what does the practices? What do your process? What's the culture change? So we were engaging with some customers, and then we were seeing that some of our customers back then, even we're doing bits and pieces off. This isthe well because there's a lot of practice and a lot of knowledge around. How did the autonomous count management and at the same time that we talked about the other customers who not yet on a charity who definitely want to get there? But I'm not quite sure how to do it, and I don't want to figure it out themselves. So we thought, Okay, let's take all of these best practices that we have and build more or less a methodology around it. How to make this actually works like how to do this. We really broke it down into, like, individual sprints to distance sprint one that distance sprint to to really have the results within three months, six months, twelve months. Whatever the cases that you want to run on. And then we realised talking to customers. This by itself isn't still enough. So that's why we started to open up this to an entire ecosystem. So WeII brought ecosystem partners along, like working closely with read a lot of our companies, but also system integrators who can help us. We speak of projects because we as a company, our software companies were not a services are consulting company, and we do support customer that some of those engagement. But if you think of like a really Fortune five hundred company that's a multi approaches, it will keep hundreds of people busy. So to recap like built in methodology, we built ecosystem to deliver on that promise at scale. And now the last step was we were doing this. We also built like a reference architecture for it, and I was just in an eternal ideas. So how do we, like structure this building reference architecture and then realized Okay, It's kind of like super helpful for customers. So that is why we don't decided to open source this reference architecture this fabric as well, too, like the tires after community, so they can also use it. So technically, stability is three pieces. It's the methodology, it's the ecosystem. And it's like the reference architecture that you can work with to help you, Chief. Go. >> All right, um, tell us how your a I fit into this. I've heard some analyst firms are saying, you know, some of the next generation of your space could be a I ops. Do you consider yourselves moving in that direction, or do you have some counter view on that? >> I think today a lot of things ar e I upset my now b a i ops, and it's a very undefined goal. This mentioned earlier. We decided to have aye aye based algorithms as powerful platform five years ago and nobody back then was talking about the layoffs. Funny story. Some of our competitors even told us you can't use the eye for monitoring just like totally stupid that there are other companies that they were doing it. But again, so the whole industry is learning here. I think it's really about data analysis. If you look at, if you scare the bigger and bigger environment, you really have to look at the process off what human operations people are doing on. There's obviously some hard decisions that you have to take their have. You have to work with teams to resolve our problems. But the biggest portion is really data analysis interpretation, right and a lot of this can be put into, and a I component that doesn't What's the Dyna trees, eh? I does it more. This is like your saree in codes, so to speak, which is able to find what's broken in the education, what was related to an issue in the application and being able to automatically find the root cause. Very importantly, we're kind of like opinionated and how in a I for operational practices should be working because one thing you don't want it serious you want? Don't want it happening. Iop system tell you well, you should. We start this service because some neural and that were told to do so. That's a building, a lot of confidence. That's why our approach is really tio follow. Like what we call a deterministic a pia a sari. And hey, I did it able to explain back to the user White came to a certain conclusion. So why should their we sort this herb is west of the rollback, this deployment or why that's the I b. Believe that if I fixed this problem, then like the bigger problem will be solved. So that's our approach, Teo T. I actually started like, roughly four years ago, five years ago, even a bit more than that on you. And I think that have a lot of experience, really rolling it out its scale and seeing it will help people because the next the ultimate next question, without always Scott Wass. If you wanna know what the problem is, why don't you fix it? And that's exactly the conversation you want to have, maybe just briefly at here, because it usually comes up okay, f a I and isat replacing people's jobs? I don't think so. We also heard it in the keynote today from Chris. It's augmenting our capabilities. There's hard decisions that you have to take, but just going through tons and tons of data. It's not going to your isn't very often when we talked at operations team or almost every time. First of all, you can't hire enough people anyways to get all the old done that's on your plate. Secondly, um, just by the amount of data and the time that I had to react. It's just long with a human understanding scenario way. Do this demo on self healing, often application. Where were deployed, something broken into production and have it being rolled back and we can do fifty one seconds. No human can do it that fast. That's just what pure, softer automation can do for you. So I think that then you can focus on other areas and more important, new project with us people in on the off space. What's what the three projects that you want to work and you never have time to work out and usually come up with the list. Yet this is what we give you back that time to work on exactly the things that move your business forwards. You >> said fifty one seconds. You've never seen Stew in action. You still have a lot of confidence. >> Well, we we love the machine, enhance human intelligence. You're definitely We could all use those machines to help us all get away from the drudgery and be able to do more. >> Always safe travels. Thanks for being with us. Headed back to Austria. Say, hide all your folks back in Austria, right There always is on his way home on his way to the airport. Thank you for being with us here on the Cube. Thanks. Appreciate the time our coverage continues here. Red hat some twenty nineteen. You're watching the cube?

>> Narrator: Live from the Moscone Center, it's theCube, covering AWS Summit San Francisco 2018 brought to you by Amazon Web Services. (upbeat music) >> We're back I'm Stu Miniman and we're here with theCube's exclusive coverage of AWS Summit San Francisco here in the Moscone Center West. Happy to welcome to the program two gentlemen from DynaTrace, we've got Andy Grabner, who's a DevOps specialist and Dave Anderson, vice president of marketing. Gentlemen, thanks so much for joining us. >> Thanks for having us. >> Alright so Dave we'll start, since you've got the marketing title, give us a little bit your role there and for our audience that might not be familiar with DynaTrace, I'm sure everybody knows 'em, but give us a little bit of the background. >> So essentially what DynaTrace does is, the world needs software to work perfectly. What we do is we help customers build and manage their software in their cloud environments on premise to help deliver a fantastic customer experiences because we know that it all needs to work. We've been in the market for the Magic Quadrant leader for the last eight years in the APM space, but we're expanding out beyond that now as the customer demands. >> Excellent, well one of my favorite lines you say you have to make software work, is they said hardware will eventually fail and software will eventually work. So Andy you've given a session here at the show tell us what your role is at DynaTrace, what are you doing here at the show? >> So I've been with the company for 10 years and I've been through a similar transformation that I believe most of the people here want to go through from quote unquote old-fashion, on premise, legacy, monolithic applications to using containers, microservices, and eventually serverless. So my session was all about fearless from monolith to serverless. I gave them some ideas on what we went through, how we as a company transformed, but also how our product transformed from, before we did on premise monitoring, built for the monolithic apps, and now we basically do full cloud-scale, in the cloud, but still covering all the enterprise technology because everybody that wants to build the cool, new stuff that they are selling here, you still have legacy applications that you integrate with and still carry around. So it's all about enterprise cloud technology that we cover. >> So Dave I hear all this I'm sure DynaTrace has more than 10 years of server-less and 12 factor authentication experience, right? >> Dave: Yes. >> Okay so you're the hipster you know, a cloud native company, you were doing all of it before any of us knew about exists. Tell us a little bit, historically, how did DynaTrace start before and move into this space? >> Yeah, so we've been in the space for around 10 years. We've been a leader in the space, but what we really did four or five years ago is we predicted on the future we were going to have serverless environments, we're going to have microservices, customers are going to have multiple cloud environments, they're going to need that software to work and they're going to need automation. So what we did is we took our 50 best engineers and we said go and re-invent the future and that's exactly what they've done. Our CTO has a vision, fully automated IT, so our whole product philosophy is around making it really simple for our customers to be able to see within this really complex digital environment, exactly what's going on, how is the software performing, how are the users adopting it and how do we role out better features and better functions to the customer base. >> All right, I love the re-invent pun, but this is the Summit, ReInvent's in November. Andy, we were talking to Sandy Carter, in the last segment, talking about customers and customers have so many applications that it's great to say this is the future and serverless and micro-architectures distributed is great and everything, but some of your stuff's going to be lift and shift, some of the stuff's probably got to stay where it is for a while, how do customers manage that portfolio and a few years ago it was like, we're going to do a bi-model world, we were not onboard with that, but there's a spectrum and there's lots of applications and it's really complicated, so what is the advice, how do you help customers kind of squint through that, and work through that? >> So I think essentially people want to update the critical apps, be more innovative, they want to go and invest in the new enterprise clouds tech, I would say, right? So we basically help them, first of all, figure out which of the applications that they have right now are easier to migrate, whether it's lift and shift or re-platform because we actually give them full visibility into the current tech, tell them where are the most dependent and least dependent services, which ones are easier to extract and harder to extract, depending on the dependencies and the traffic take us over into criticalities. So we help them first of all figure out their cloud migration plan, what to migrate first. We talked about T-shirt sizing your migration, small, medium, and large, and then not only do we help them to migrate things over but to break the big monoliths apart put stuff on top of it, right? So this is also happening, so we really help them to figure out which application, which service to tackle first, to migrate over. We do it in a safe way because we not only help them to later on monitor their new system, but we help them along the way. So we talked about DevOps earlier. I mean we had our little prep call. We actually think that monitoring, the space we are, is not just something to keep the lights on in production, but it's something that has to be checked along the delivery pipeline. That's why we are part of the development process, we are apart of your CICD, when a code change goes in, an architectural change goes in, when they move over, we monitor all these changes and we give you early warning signals that this change is going to be good one or not a good one. And that's how we solve them. >> Well so much things in the cloud, it's never a one time thing, it's got to be an ongoing process, it's iterative and if I hear right though, you're not just only an AWS, it's my on premises stuff, multi-cloud, you play with all of those environments. >> Yes. Yes exactly so I mean you name it. I'm not sure if I'm allowed to name all the other vendors in this space here at AWS. >> Look we're independent media, we cover all of those shows, and I think your customers are using all them, so you can say, they're all in an AWS, but they might also use GCP and Azure and other stuff. >> I think the stats were like 98 or 90% of customers are hybrid enterprise, multi-cloud, and that's why we designed the product to be able to do just that. They're going to have applications running in the cloud that are making calls back to things on premise. You want to be able to see that entire delivery chain. So absolutely we provide that single visibility across all of their cloud environments and on premise. >> What are you seeing as some of the biggest challenges your customers are facing, Dave? >> The shear, the complexity, the pressures which they face, which is they've got to shift to the cloud faster. They've got their CEO going, we need to provide better digital experience. They're going to build out these new cloud platforms. They're just struggling for time to deploy these things. They need to move faster. There's threats of competition, all the buzzwords that come, but they're all real for IT people. And then all we're doing is giving them that visibility because the environments have become so complex, microservice, serverless, multi-cloud, on-premise, and just to be able to help them challenge the visibility into where is everything, how is it performing, is it working and then give them the confidence to release faster as Andy talks about. >> So Andy, one of the things that people look at sometimes is okay it's a multi-cloud environment, but okay if I go down the container environment, can I do that multi-cloud? If I go down the path of say something like Fargate, that's only with Amazon, so are your customers concerned about that, how deep down do they go? I should say, how far up the stack are they willing to go with Amazon or are they holding back and trying to use services that are more easy to be able to be migrated if need be? >> I want to give you two answers to this. >> Yeah. >> First of all, the developers don't care. >> Okay. >> I don't care where it runs. >> No, I understand. I've got a software development team. When they port it over to any of us, they're like autoscaling's awesome, it's great, I don't want to have to port somewhere else, and if it works, I go back to, it was like, standards and proprietary versus that if you solve my business need, I'm needed. So I agree, but, what's your other answer? >> Yeah so but it is clear that people, what we hear at least, what I hear, people want to figure out, how can they define their next platform and make sure that at least they're not doing a complete vendor lock in, a cloud lock in, so they definitely think and invest in, how can we deliver something, a platform to our developers so that they can just worry about writing code and we make sure that, if we decide Amazon today, maybe something else later, it's not going to be too hard and so I think we see the people try, I think still a lot of people are in the early stages. So they start primarily with one vendor, with one platform, with one technology, but they always make sure that they keep their options open to eventually move over and they're constantly look, that's why they're constantly bringing in new technology, which is also a challenge for every vendor that is here on the floor to make sure we're coping with this technology disruption that is constantly happening, not only for the users, the consumers of the technology, but those of us as vendors and I think that's what we try to keep up with, yeah? >> Yeah, so how we doing as industry and how are customers doing at keeping up with all this change? >> It is, I think, constant dedication, constantly looking what's new. We, as Dave mentioned, we until only a couple of years ago figured out something new is coming, so we actually broke out our own team, our innovation team, that figure out what's the next big thing, I think we see this also with our customers. You constantly have to disrupt yourself, you constantly have to redefine yourself and that's what we did with monitoring. We redefined monitoring because we saw five years ago that a new wave of technology's coming and we don't stop now, we keep innovating and everybody else is doing it as well. You always have to keep up with what's coming and experiment and figure out what makes sense for you and what maybe does not make sense for you. You don't have to be part of every hype. >> And we do that in two ways, we sort of do that also in that a lot of the features that we put into the product actually come from our customer base. So we have a really strong connection with our customers, we listen to the customers, and we say, what do you need, what challenges are you suffering, what would you like to have, and then we build them into our product roadmap. So it's kind of a hybrid model of making sure you're able to listen to the customer and take their needs in, but also sometimes they don't know what's coming, so we'd work with an AWS, to understand what they're building out, and other technology partners to make sure that our product is future proof. >> So when you built that innovation team and everything, is it serverless underneath now for some of your products? >> It's a set of technologies, right? It's all of what you basically see here on the floor and others. I think the nice thing, what I heard actually today on the floor, they said you don't only talk about DevOps and CICD and innovation, you actually live it and what they mean with this, he said, if I look at how often DynaTrace produces new features, we deploy new feature releases twice a month, we deploy daily new updates, and then they said, if you look at other vendors in this space they also claim to be living what they expect from you, but they deploy twice a year still or maybe every other month. So I think we redefined monitoring, but also redefined and live what we actually expect our customers to do. >> Yeah, if you say you're a DevOps company, you better be embracing CICD and publish now and often. All right, Andy and Dave, thank you so much for giving us the updates. Congrats on the progress, we look forward to catching with you up more in the future. We'll be back with lots more coverage here from AWS Summit San Francisco, I'm Stu Miniman. You're watching theCube. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The technology spending outlook is not pretty and very much unpredictable right now. The negative sentiment is of course being driven by the macroeconomic factors in earnings forecasts that have been coming down all year in an environment of rising interest rates. And what's worse, is many people think earnings estimates are still too high. But it's understandable why there's so much uncertainty. I mean, technology is still booming, digital transformations are happening in earnest, leading companies have momentum and they got cash runways. And moreover, the CEOs of these leading companies are still really optimistic. But strong guidance in an environment of uncertainty is somewhat risky. Hello and welcome to this week's Wikibon CUBE Insights Powered by ETR. In this breaking analysis, we share takeaways from ETR'S latest spending survey, which was released to their private clients on October 21st. Today, we're going to review the macro spending data. We're going to share where CIOs think their cloud spend is headed. We're going to look at the actions that organizations are taking to manage uncertainty and then review some of the technology companies that have the most positive and negative outlooks in the ETR data set. Let's first look at the sample makeup from the latest ETR survey. ETR captured more than 1300 respondents in this latest survey. Its highest figure for the year and the quality and seniority of respondents just keeps going up each time we dig into the data. We've got large contributions as you can see here from sea level executives in a broad industry focus. Now the survey is still North America centric with 20% of the respondents coming from overseas and there is a bias toward larger organizations. And nonetheless, we're still talking well over 400 respondents coming from SMBs. Now ETR for those of you who don't know, conducts a quarterly spending intention survey and they also do periodic drilldowns. So just by the way of review, let's take a look at the expectations in the latest drilldown survey for IT spending. Before we look at the broader technology spending intentions survey data, followers of this program know that we reported on this a couple of weeks ago, spending expectations that peaked last December at 8.3% are now down to 5.5% with a slight uptick expected for next year as shown here. Now one CIO in the ETR community said these figures could be understated because of inflation. Now that's an interesting comment. Real GDP in the US is forecast to be around 1.5% in 2022. So these figures are significantly ahead of that. Nominal GDP is forecast to be significantly higher than what is shown in that slide. It was over 9% in June for example. And one would interpret that survey respondents are talking about real dollars which reflects inflationary factors in IT spend. So you might say, well if nominal GDP is in the high single digits this means that IT spending is below GDP which is usually not the case. But the flip side of that is technology tends to be deflationary because prices come down over time on a per unit basis, so this would be a normal and even positive trend. But it's mixed right now with prices on hard to find hardware, they're holding more firms. Software, you know, software tends to be driven by lock in and competition and switching costs. So you have those countervailing factors. Services can be inflationary, especially now as wages rise but certain sectors like laptops and semis and NAND are seeing less demand and maybe even some oversupply. So the way to look at this data is on a relative basis. In other words, IT buyers are reporting 280 basis point drop in spending sentiment from the end of last year. Now, something that we haven't shared from the latest drilldown survey which we will now is how IT bar buyers are thinking about cloud adoption. This chart shows responses from 419 IT execs from that drilldown and depicts the percentage of workloads their organizations have in the cloud today and what the expectation is through years from now. And you can see it's 27% today and it's nearly 50% in three years. Now the nuance is if you look at the question, that ETRS, it's they asked about IaaS and PaaS, which to some could include on-prem. Now, let me come back to that. In particular, financial services, IT, telco and retail and services industry cited expectations for the future for three years out that we're well above the average of the mean adoption levels. Regardless of how you interpret this data there's most certainly plenty of public cloud in the numbers. And whether you believe cloud is an operating environment or a place out there in the cloud, there's plenty of room for workloads to move into a cloud model well beyond mid this decade. So you know, as ho hum as we've been toward recent as-a-service models announced from the likes of HPE with GreenLake and Dell with APEX, the timing of those offerings may be pretty good actually. Now let's expand on some of the data that we showed a couple weeks ago. This chart shows responses from 282 execs on actions their organizations are taking over the next three months. And the Deltas are quite traumatic from the early part of this charter than the left hand side. The brown line is hiring freezes, the black line is freezing IT projects, and the green line is hiring increases and that red line is layoffs. And we put a box around the sort of general area of the isolation economy timeframe. And you can see the wild swings on this chart. By mid last summer, people were kickstarting things and more hiring was going on and the black line shows IT project freezes, you know, came way down. And now, or on the way back up as our hiring freezes. So we're seeing these wild swings in organizational actions and strategies which underscores the lack of predictability. As with supply chains around the world, this is likely due to the fact that organizations, pre pandemic they were optimized for efficiency, not a lot of waste rather than business resilience. Meaning, you know, there's again not a lot of fluff in the system or if there was it got flushed out during the pandemic. And so the need for productivity and automation is becoming increasingly important, especially as actions that solely rely on headcount changes are very, very difficult to manage. Now, let's dig into some of the vendor commentary and take a look at some of the names that have momentum and some of the others possibly facing headwinds. Here's a list of companies that stand out in the ETR survey. Snowflake, once again leads the pack with a positive spending outlook. HashiCorp, CrowdStrike, Databricks, Freshworks and ServiceNow, they round out the top six. Microsoft, they seem to always be in the mix, as do a number of other security and related companies including CyberArk, Zscaler, CloudFlare, Elastic, Datadog, Fortinet, Tenable and to a certain extent Akamai, you can kind of put them sort of in that group. You know, CDN, they got to worry about security. Everybody worries about security, but especially the CDNs. Now the other software names that are highlighted here include Workday and Salesforce. On the negative side, you can see Dynatrace saw some negatives in the latest survey especially around its analytics business. Security is generally holding up better than other sectors but it's still seeing greater levels of pressure than it had previously. So lower spend. And defections relative to its observability peers, that's really for Dynatrace. Now the other one that was somewhat surprising is IBM. You see the IBM was sort of in that negative realm here but IBM reported an outstanding quarter this past week with double digit revenue growth, strong momentum in software, consulting, mainframes and other infrastructure like storage. It's benefiting from the Kyndryl restructuring and it's on track IBM to deliver 10 billion in free cash flow this year. Red Hat is performing exceedingly well and growing in the very high teens. And so look, IBM is in the midst of a major transformation and it seems like a company that is really focused now with hybrid cloud being powered by Red Hat and consulting and a decade plus of AI investments finally paying off. Now the other big thing we'll add is, IBM was once an outstanding acquire of companies and it seems to be really getting its act together on the M&A front. Yes, Red Hat was a big pill to swallow but IBM has done a number of smaller acquisitions, I think seven this year. Like for example, Turbonomic, which is starting to pay off. Arvind Krishna has the company focused once again. And he and Jim J. Kavanaugh, IBM CFO, seem to be very confident on the guidance that they're giving in their business. So that's a real positive in our view for the industry. Okay, the last thing we'd like to do is take 12 of the companies from the previous chart and plot them in context. Now these companies don't necessarily compete with each other, some do. But they are standouts in the ETR survey and in the market. What we're showing here is a view that we like to often show, it's net score or spending velocity on the vertical axis. And it's a measure, that's a measure of the net percentage of customers that are spending more on a particular platform. So ETR asks, are you spending more or less? They subtract less from the mores. I mean I'm simplifying, but that's what net score is. Now in the horizontal axis, that is a measure of overlap which is which measures presence or pervasiveness in the dataset. So bigger the better. We've inserted a table that informs how the dots in the companies are positioned. These companies are all in the green in terms of net score. And that right most column in the table insert is indicative of their presence in the dataset, the end. So higher, again, is better for both columns. Two other notes, the red dotted line there you see at 40%. Anything over that indicates an highly elevated spending momentum for a given platform. And we purposefully took Microsoft out of the mix in this chart because it skews the data due to its large size. Everybody else would cluster on the left and Microsoft would be all alone in the right. So we take them out. Now as we noted earlier, Snowflake once again leads with a net score of 64%, well above the 40% line. Having said that, while adoption rates for Snowflake remains strong the company's spending velocity in the survey has come down to Earth. And many more customers are shifting from where they were last year and the year before in growth mode i.e. spending more year to year with Snowflake to now shifting more toward flat spending. So a plus or minus 5%. So that puts pressure on Snowflake's net score, just based on the math as to how ETR calculates, its proprietary net score methodology. So Snowflake is by no means insulated completely to the macro factors. And this was seen especially in the data in the Fortune 500 cut of the survey for Snowflake. We didn't show that here, just giving you anecdotal commentary from the survey which is backed up by data. So, it showed steeper declines in the Fortune 500 momentum. But overall, Snowflake, very impressive. Now what's more, note the position of Streamlit relative to Databricks. Streamlit is an open source python framework for developing data driven, data science oriented apps. And it's ironic that it's net score and shared in is almost identical to those of data bricks, as the aspirations of Snowflake and Databricks are beginning to collide. Now, however, the Databricks net score has held up very well over the past year and is in the 92nd percentile of its machine learning and AI peers. And while it's seeing some softness, like Snowflake in the Fortune 500, Databricks has steadily moved to the right on the X axis over the last several surveys even though it was unable to get to the public markets and do an IPO during the lockdown tech bubble. Let's come back to the chart. ServiceNow is impressive because it's well above the 40% mark and it has 437 shared in on this cut, the largest of any company that we chose to plot here. The only real negative on ServiceNow is, more large customers are keeping spending levels flat. That's putting a little bit pressure on its net score, but that's just conservatives. It's kind of like Snowflakes, you know, same thing but in a larger scale. But it's defections, the ServiceNow as in Snowflake as well. It's defections remain very, very low, really low churn below 2% for ServiceNow, in fact, within the dataset. Now it's interesting to also see Freshworks hit the list. You can see them as one of the few ITSM vendors that has momentum and can potentially take on ServiceNow. Workday, on this chart, it's the other big app player that's above the 40% line and we're only showing Workday HCM, FYI, in this graphic. It's Workday Financials, that offering, is below the 40% line just for reference. Now let's talk about CrowdStrike. We attended Falcon last month, CrowdStrike's user conference and we're very impressed with the product visio, the company's execution, it's growing partnerships. And you can see in this graphic, the ETR survey data confirms the company's stellar performance with a net score at 50%, well above the 40% mark. And importantly, more than 300 mentions. That's second only to ServiceNow, amongst the 12 companies that we've chosen to highlight here. Only Microsoft, which is not shown here, has a higher net score in the security space than CrowdStrike. And when it comes to presence, CrowdStrike now has caught up to Splunk in terms of pervasion in the survey. Now CyberArk and Zscaler are the other two security firms that are right at that 40% red dotted line. CyberArk for names with over a hundred citations in the security sector, is only behind Microsoft and CrowdStrike. Zscaler for its part in the survey is seeing strong momentum in the Fortune 500, unlike what we said for Snowflake. And its pervasion on the X-axis has been steadily increasing. Again, not that Snowflake and CrowdStrike compete with each other but they're too prominent names and it's just interesting to compare peers and business models. Cloudflare, Elastic and Datadog are slightly below the 40% mark but they made the sort of top 12 that we showed to highlight here and they continue to have positive sentiment in the survey. So, what are the big takeaways from this latest survey, this really quick snapshot that we've taken. As you know, over the next several weeks we're going to dig into it more and more. As we've previously reported, the tide is going out and it's taking virtually all the tech ships with it. But in many ways the current market is a story of heightened expectations coming down to Earth, miscalculations about the economic patterns and the swings and imperfect visibility. Leading Barclays analyst, Ramo Limchao ask the question to guide or not to guide in a recent research note he wrote. His point being, should companies guide or should they be more cautious? Many companies, if not most companies, are actually giving guidance. Indeed, when companies like Oracle and IBM are emphatic about their near term outlook and their visibility, it gives one confidence. On the other hand, reasonable people are asking, will the red hot valuations that we saw over the last two years from the likes of Snowflake, CrowdStrike, MongoDB, Okta, Zscaler, and others. Will they return? Or are we in for a long, drawn out, sideways exercise before we see sustained momentum? And to that uncertainty, we add elections and public policy. It's very hard to predict right now. I'm sorry to be like a two-handed lawyer, you know. On the one hand, on the other hand. But that's just the way it is. Let's just say for our part, we think that once it's clear that interest rates are on their way back down and we'll stabilize it under 4% and we have clarity on the direction of inflation, wages, unemployment and geopolitics, the wild swings and sentiment will subside. But when that happens is anyone's guess. If I had to peg, I'd say 18 months, which puts us at least into the spring of 2024. What's your prediction? You know, it's almost that time of year. Let's hear it. Please keep in touch and let us know what you think. Okay, that's it for now. Many thanks to Alex Myerson. He is on production and he manages the podcast for us. Ken Schiffman as well is our newest addition to the Boston Studio. Kristin Martin and Cheryl Knight, they help get the word out on social media and in our newsletters. And Rob Hoff is our EIC, editor-in-chief over at SiliconANGLE. He does some wonderful editing for us. Thank you all. Remember all these episodes, they are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me at david.vellante@siliconangle.com or DM me @dvellante. Or feel free to comment on our LinkedIn posts. And please do check out etr.ai. They've got the best survey data in the enterprise tech business. If you haven't checked that out, you should. It'll give you an advantage. This is Dave Vellante for theCUBE Insights Powered by ETR. Thanks for watching. Be well and we'll see you next time on Breaking Analysis. (soft upbeat music)

>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Despite fears of inflation, supply chain issues skyrocketing energy and home prices and global instability caused by the Ukraine crisis CIOs and IT buyers continue to expect overall spending to increase more than 6% in 2022. Now, while this is lower than our 8% prediction that we made earlier this year in January, it remains in line with last year's roughly six to 7% growth and is holding firm with the expectations reported by tech executives on the ETR surveys last quarter. Hello and welcome to this week's wiki bond cube insights powered by ETR in this breaking analysis, we'll update you on our latest look at tech spending with a preliminary take from ETR's latest macro drill down survey. We'll share some insights to which vendors have shown the biggest change in spending trajectory. And we'll tap our technical analysts to get a read on what they think it means for technology stocks going forward. The IT spending sentiment among IT buyers remains pretty solid. >> In the past two months, we've had conversations with dozens of CIOs, chief digital officers data executives, IT managers, and application developers, and across the board, they've indicated that for now at least their spending levels remain largely unchanged. The latest ETR drill down data which will share shortly, confirms these anecdotal checks. However, the interpretation of this data it's somewhat nuanced. Part of the reason for the spending levels being you know reasonably strong and holding up is inflation. Stuff costs more so spending levels are higher forcing IT managers to prioritize. Now security remains the number one priority and is less susceptible to cuts, cloud migration, productivity initiatives and other data projects remain top priorities. >> So where are CIO's robbing from Peter to pay Paul to focus on these priorities? Well, we've seen a slight uptick in certain speculative. IT projects being put on hold or frozen for a period of time. And according to ETR survey data we've seen some hiring freezes reported and this is especially notable in the healthcare sector. ETR also surveyed its buyer base to find out where they were adjusting their budgets and the strategies and tactics they were using to do so. Consolidating IT vendors was by far the most cited tactic. Now this makes sense as companies in an effort to negotiate better deals will often forego investments in newer so-called best of breed products and services, and negotiate bundles from larger suppliers. You know, even though they might not be as functional, the buyers >> can get a better deal if they bundle together from one of their larger suppliers. Think Microsoft or a Dell or other, you know, large companies. ETR survey respondents also cited cutting the cloud bill where discretionary spending was in play was another strategy or tactic that they were using. We certainly saw this with some of the largest snowflake customers this past quarter. Where even though they were still growing consumption rapidly certain snowflake customers dialed down their consumption and pushed spending off to future quarters. Now remember in the case of snowflake, anyway, customers negotiate consumption rates and their pricing based on a total commitment over a period of time. So while they may consume less in one quarter, over the lifetime of the contract, snowflake, as do many other cloud companies, have good visibility on the lifetime value of a deal. Now this next chart shows the latest ETR spending expectations among more than 900 respondents. The bars represent spending growth expectations from the periods of December, 2021 that's the gray bars, March of 2022 survey in the blue, and the most recent June data, That's the yellow bar. So you can see spending expectations for the quarter is down slightly in the mid 5% range. But overall for the year expectations remain in the mid 6% range. Now it's down from 8%, 8.3% in December where it looked like 2022 was going to really be a breakout year and have more momentum than even last year. Now, remember this was before Russia invaded Ukraine which occurred in mid-February of this year. So expectations were a little higher. So look, generally speaking CIOs have told us that their CFOs and CEOs have lowered their earnings outlooks and communicated that to Wall Street. They've told us that unless and until these revised forecasts appear at risk, they continue to expect their budget levels to remain pretty constant. Now there's still plenty of momentum and spending velocity on specific vendor platforms. Let's take a look at that. >> This chart shows the companies with the greatest spending momentum as measured by ETRs proprietary net score methodology. Net score essentially measures the net percent of customers spending more on a particular platform. That measurement is shown on the Y axis. The red line there that's inserted that red dotted line at 40%, we consider to be a highly elevated mark. And the green dots are companies in the ETR survey that are near or above that line. The X axis measures the presence in the data set, how much, you know sort of pervasiveness, if you will, is in the data. It's kind of a proxy for market presence. Now, of course we all know Kubernetes is not a company, but it remains an area where organizations are spending lots of resources and time particularly to modernize and mobilize applications. Snowflake remains the company which leads all firms in spending velocity, but as you'll see momentarily, despite its highest position relative to everybody else in the survey, it's still down from its previous levels in the high seventies and low 80% range. AWS is incredibly impressive because it has an elevated level but also a big presence in the data set in the survey. Same with Microsoft, same with ServiceNow which also stands out. And you can see the other smaller vendors like HashiCorp which is increasingly being seen as a strategic cross cloud enabler. They're showing, spending momentum. The RPA vendors you see in there automation anywhere and UI path are in the mix with numerous security companies, CrowdStrike, CyberArk, Netskope, Cloudflare, Tenable Okta, Zscaler Palo Alto networks, Sale Point Fortunate. A big number of cybersecurity firms hovering at or above that 40% mark you can see pure storage remains elevated as do PagerDuty and Coupa. So plenty of good news here, despite the recent tech crash. So that was the good, here's the not so good. So >> there is no 40% line on this chart because all these companies are well below that line. Now this doesn't mean these companies are bad companies. They just don't have the spending velocity of the ones we showed earlier. A good example here is Oracle. Look how they stand out on the X axis with a huge market presence. And Oracle remains an incredibly successful company selling to high end customers and really owning that mission critical data and application space. And remember ETR measures spending activity, but not actual spending dollars. So Oracle is skewed as a result because Oracle customers spend big bucks. But the fact is that Oracle has a large legacy install base that pulls down their growth rates. And that does show up in the ETR survey data. Broadcom is another example. They're one of the most successful companies in the industry, and they're not going after growth at all costs at all. They're going after EBITDA and of course ETR doesn't measure EBIT. So just keep that in mind, as you look at this data. Now another way to look at the data and the survey, is exploring the net score movement over the last period amongst companies. So how are they moving? What's happening to the net score over time. And this chart shows the year over year >> net score change for vendors that participate in at least three sectors within the ETR taxonomy. Remember ETR taxonomy has 12, 15 different segments. So the names above or below the gray dotted line are those companies where the net score has increased or decreased meaningfully. So to the earlier chart, it's all relative, right? Look at Oracle. While having lower net scores has also shown a more meaningful improvement in net score than some of the others, as have SAP and Teradata. Now what's impressive to me here is how AWS, Microsoft, and Google are actually holding that dotted line that gray line pretty well despite their size and the other ironically interesting two data points here are Broadcom and Nutanix. Now Broadcom, of course, as we've reported and dug into, is buying VMware and, and of, of course most customers are concerned about getting hit with higher prices. Once Broadcom takes over. Well Nutanix despite its change in net scores, in a good position potentially to capture some of that VMware business. Just yesterday, I talked to a customer who told me he migrated his entire portfolio off VMware using Nutanix AHV, the Acropolis hypervisor. And that was in an effort to avoid the VTEX specifically. Now this was a smaller customer granted and it's not representative of what I feel is Broadcom's ICP the ideal customer profile, but look, Nutanix should benefit from the Broadcom acquisition. If it can position itself to pick up the business that Broadcom really doesn't want. That kind of bottom of the pyramid. One person's trash is another's treasure as they say, okay. And here's that same chart for companies >> that participate in less than three segments. So, two or one of the segments in the ETR taxonomy. Only three names are seeing positive movement year over year in net score. SUSE under the leadership of amazing CEO, Melissa Di Donato. She's making moves. The company went public last year and acquired rancher labs in 2020. Look, we know that red hat is the big dog in Kubernetes but since the IBM acquisition people have looked to SUSE as a possible alternative and it's showing up in the numbers. It's a nice business. It's going to do more than 600 million this year in revenue, SUSE that is. It's got solid double digit growth in kind of the low teens. It's profitability is under pressure but they're definitely a player that is found a niche and is worth watching. The SolarWinds, What can I say there? I mean, maybe it's a dead cat bounce coming off the major breach that we saw a couple years ago. Some of its customers maybe just can't move off the platform. Constant contact we really don't follow and don't really, you know, focus on them. So, not much to say there. Now look at all the high priced earning stocks or infinite PE stocks that have no E and divide by zero or a negative number and boom, you have infinite PE and look at how their net scores have dropped. We've reported extensively on snowflake. They're still number one as we showed you earlier, net score, but big moves off their highs. Okta, Datadog, Zscaler, SentinelOne Dynatrace, big downward moves, and you can see the rest. So this chart really speaks to the change in expectations from the COVID bubble. Despite the fact that many of these companies CFOs would tell you that the pandemic wasn't necessarily a tailwind for them, but it certainly seemed to be the case when you look back in some of the ETR data. But a big question in the community is what's going to happen to these tech stocks, these tech companies in the market? We reached out to both Eric Bradley of ETR who used to be a technical analyst on Wall Street, and the long time trader and breaking analysis contributor, Chip Symington to get a read on what they thought. First, you know the market >> first point of the market has been off 11 out of the past 12 weeks. And bare market rallies like what we're seeing today and yesterday, they happen from time to time and it was kind of expected. Chair Powell's testimony was broadly viewed as a positive by the street because higher interest rates appear to be pushing commodity prices down. And a weaker consumer sentiment may point to a less onerous inflation outlook. That's good for the market. Chip Symington pointed out to breaking analysis a while ago that the NASDAQ has been on a trend line for the past six months where its highs are lower and the lows are lower and that's a bad sign. And we're bumping up against that trend line here. Meaning if it breaks through that trend it could be a buying signal. As he feels that tech stocks are oversold. He pointed to a recent bounce in semiconductors and cited the Qualcomm example. Here's a company trading at 12 times forward earnings with a sustained 14% growth rate over the next couple of years. And their cash flow is able to support their 2.4, 2% annual dividend. So overall Symington feels this rally was absolutely expected. He's cautious because we're still in a bear market but he's beginning to, to turn bullish. And Eric Bradley added that He feels the market is building a base here and he doesn't expect a 1970s or early 1980s year long sideways move because of all the money that's still in the system. You know, but it could bounce around for several months And remember with higher interest rates there are going to be more options other than equities which for many years has not been the case. Obviously inflation and recession. They are like two looming towers that we're all watching closely and will ultimately determine if, when, and how this market turns around. Okay, that's it for today. Thanks to my colleagues, Stephanie Chan, who helps research breaking analysis topics sometimes, and Alex Myerson who is on production in the podcast. Kristin Martin and Cheryl Knight they help get the word out and do all of our newsletters. And Rob Hof is our Editor in Chief over at siliconangle.com and does some wonderful editing for breaking analysis. Thank you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search breaking analysis podcasts. I publish each week on wikibon.com and Siliconangle.com. And of course you can reach me by email at david.vellante@siliconangle.com or DM me at DVellante 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 the CUBE insights powered by ETR. Stay safe, be well. And we'll see you next time. (soft music)

(upbeat music) >> Full stack observability is all the rage today. As businesses lean into digital, customer experience becomes ever more important. Why? Well, it's obvious, fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades old software companies that have traditionally done monitoring or log analytics and or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose-built tools that attack one particular segment of the marketplace. And now they're pivoting through M&A and some organic development trying to fill gaps in their portfolio. And then, you got all these new entrants coming to the market, claiming end to end visibility across the so-called modern cloud and now edge native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem. But, you know, recent survey research from ETR confirms our thesis that no one company has it all. Here's the thing. Customers just want to figure out the root cause as quickly and as efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante and welcome to this special Cube presentation where we dig into root cause analysis, and specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. And in this session, we have two deep dives. First, we're going to dig into this exciting new field of RCaaS, Root Cause As A Service with two of the founders and technical experts behind Zebrium. And then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well known Cisco product lines, including WebEx Client and UCS. I was pretty amazed at the results and I think you'll be impressed as well. So thanks for being here. Let's get started. With me right now is Larry Lancaster, who's a founder and CTO of Zebrium. And he's joined by Rod Bagg, who's the founder and vice president of engineering at the company. Gents, welcome. Thanks for coming on. >> Thanks. >> Okay. >> It's good to be here. >> It's good to be here >> All right Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO. What do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive uptime and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web and that's how you get a point click. Or the business depends on, you know, internal systems to drive their business and to run it. When that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic and maybe it took a couple of people to maintain it and keep it running. There wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it But there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong but you got to know why. And it's our contention here that, you know, really, when you take a look at the observability space, you have metrics, that's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know where it's happening or where something is running slow, potentially. So that's great. But again, the root cause of why it's happening is going to be buried in log files. And I can expand on that a little bit more but you know, when you're a software developer and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing, or why it went wrong. And it's that that really gets you to the root cause very fast. And that's our contention, is that these software systems are so complex nowadays and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you are just doomed for failure. And that's where we come in. >> Great. >> Getting to that root cause. >> Thank you, Rod. You know, it's interesting you talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose probably closer to a trillion dollars a year in breaches. And there's a similar analogy here. 20 billion could be 5X in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCaaS. What does it mean? What problems does it solve, and how does it solve the problem? Let's get into it. >> Yeah. Hey, thanks, Dave. So I think when you said, you know, who's automating the observer, that that's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience. That's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time. And until Zebrium came along, I would argue, no one's really done it right. So, you know, I think it's also important you know, as we step back, we can probably look forward five to 10 years and say, everyone's going to look back and say how did we do all this manually? You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just... They're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard and we don't care what kind of a dashboard it is. It could be, you know Datadog, New Relic, Elastic, Dynatrace, Grafana AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff. Yep. >> Yeah. So, interesting. Again, another analogy I think about. You know, you talked about automation. If we're to look back and say this is what... We're never going to do this again, it's like provisioning loans. Nobody provisions loans anymore, it's all automated. >> Larry: (chuckling) That's right. >> So Larry, I'll stay with you, then the skeptic in me says, this sounds amazing, but if I, you know... It might be too good to be true. Tell us how it works. >> Larry: (chuckling) Yeah. So that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months and they did a very detailed study. And they got together 192 incidents across four product lines, where they knew that the root cause was in the logs. And they knew what that root cause was because they had had their best engineers, you know work on those cases and take detailed notes of the incidents that had taken place. And so they ran that data through the Zebrium software. And what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo command center, you know when they finally, you know, touchdown on the moon kind of thing. So, you know, it's really an exciting point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business, they're an S3 competitor. Zoom has their files stored on Lyve Cloud, you know, to let you know who they are. So essentially, what happened was they were in alpha, their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored. And it was, you know, fortunately for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on. But they were scared, because they realized, if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium. They went and did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they had had. And what they saw was immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Dave: Yeah. That's great. I mean, you guys are jumping up and down, I'm sure. We're going to hear from Cisco later. I bet you, they were jumping up and down too because they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that, or actually, you guys both talked about that your tool is agnostic. So how does one actually use the service? How do I deploy it? >> Yeah. So let me step back. So when we talk about logs right? Like, you know, all these bread crumbs being in logs and everything else? So, you know, they are a great wealth of you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our... Or we've heard from several of our customers now prior to using Zebrium, when they, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metric has, you know, taken a blip or something's happened that they know there's a problem. We've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are, to get to them, maybe searching in a log manager. Just to get into the right context, even, can take hours. So, you know, that's obviously the problem we solve but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put them back in the thing they don't like doing because people don't do that. They don't like doing it. So we put it up on the dashboard. So if something is going wrong with your metrics and that's the indicator, or maybe it's something with tracing that you're sort of digging through that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs, you click on one of our integrations and we integrate with all these tools that Larry's talked about. And when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. No other work could be... You can, you know, also click down and click through to us so that you land up in our portal, if you want to do some more digging around, if you need to or whatever, maybe to get some context what have you, but it's fair that if you ever need to do that, the answer should be right there on your dashboard. And that that's how we expect people to use it. We don't want them digging in logs and going through things, we want it to be right in their workflow. >> Great. Thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment in Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AI ops. Do you have some examples of those types of firms leaning into this? >> Rod: Yeah, a couple of great ones. Well, I mean, we've got many of them, but a couple that I'll touch on. We have an actual AI ops company that was looking for, you know, sort of some complimentary technology and so on. And so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment, and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know signed up and then, you know, started sending us logs. And, you know, he was hewing and hawing, saying that he was busy, like every SRE is, and that he didn't have a chance to really do much with us yet. And, you know, we were just, you know, having this conversation on the phone, and he comes to tell us that, yeah I've been busy because we had this, you know, terrible outage, like, you know, five days ago. And we said like, "Okay did you actually look on the Zebrium dashboard?" (chuckles) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company, he hadn't put that integration in, so it wasn't in his dashboard yet, but it was certainly on ours. So he went there, and he looks and he looks on the day, you know, on the time range of when he had had this incident. And right at the very top of the page on our portal was that incident with that root cause. And he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours. And we had the answer right there in five minutes, and it was crazy. And we get that kind of stories. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it. And you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Alchera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google, Google cloud, and so on. But they use our software, and they have a lot of interaction, obviously with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out your costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking. And we had that root cause report right on the screen, again within five minutes, that was pointing to an API problem with Google. And they had changed one of their APIs and Alchera was not aware of it. So their stuff was breaking because of a change downstream that we had caught. And I'll just tell you one last one because it's somewhat related to one of these cloud vendors. You know, it was a big cloud vendor who had an outage a couple of months ago. And it's interesting because, you know, a lot of our customers will set up shared Slack channels with us, where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage, and the root cause of what was going on there in AWS that was impacting our customers that was showing up in our incidents. Now we didn't obviously, you know, have the very root cause of what was going on in AWS, per se but we were getting to the root cause of why our customer's applications were failing. And that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenges is going to be getting people's attention because these SREs are so busy, their hair's on fire. >> Rod: That's it. Right. (chuckling). You know, when you say, hey, (indistinct). >> I tell you, if you get their attention, they love it. I mean, this AI ops company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found. And quite literally, the next week, they ended up signing up as a paid customer. So... >> Dave: that's great. And Larry, to give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs and you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs that people are trying not to leave. >> Larry: That's right. Absolutely. >> Dave: But close it out here. >> Yeah. I mean, that's right, you can run it on-prem. Just like we run it in our cloud, you can run it in your cloud or on your own infrastructure. Now that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it, do a POC, try it yourself. And you know, people have become so jaded by the lack of, you know, real, sort of, innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot, I'm telling you. I'm telling you right now, it works. And you'll hear more about that from one of our customers in a minute. >> All right guys, thanks so much. Great story. Really appreciate you sharing. >> Thank you. >> Yeah. Thanks Dave. Appreciate the time. >> Okay. In a moment, we're going to hear from Cisco who is the customer in this case example and a company that has... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of, like WebEx. So stay tuned and learn about how you can really take advantage of this new technology called Root Cause As A Service. You're watching theCube, the leader in enterprise and emerging tech coverage. (upbeat music)

(bright intro music) >> Full stack observability is all the rage today. As businesses lean in to digital, customer experience becomes ever more important, why? Well, it's obvious. Fickle consumers can switch brands in the blink of an eye or the click of a mouse. Technology companies have sprung into action, and the observability space is getting pretty crowded in an effort to simplify the process of figuring out the root cause of application performance problems without an army of PhDs and lab coats, also known as endlessly digging through logs, for example. We see decades-old software companies that have traditionally done monitoring or log analytics and/or application performance management stepping up their game. These established players, you know, they typically have deep feature sets and sometimes purpose built tools that attack one particular segment of the marketplace, and now, they're pivoting through M&A and some organic development trying to fill gaps in their portfolio, and then you got all these new entrants coming to the market claiming end to end visibility across the so-called modern cloud and now edge-native stacks. Meanwhile, cloud players are gaining traction and participating through a combination of native tooling combined with strong ecosystems to address this problem, but, you know, recent survey research from ETR confirms our thesis that no one company has at all. Here's the thing. Customers just want to figure out the root cause as quickly and efficiently as possible. It's one thing to observe the stack end to end, but the question is who is automating the observers? And that's why we're here today. Hello, my name is Dave Vellante, and welcome to this special "CUBE" presentation where we dig into root cause analysis and, specifically, how one company, Zebrium, is using unsupervised machine learning to detect anomalies and pinpoint root causes and delivering it as an automated service. In this session, we have two deep dives. First, we're going to dig into this exciting new field of RCA, root cause as a service, with two of the founders and technical experts behind Zebrium, and then we bring in two technical experts from Cisco, an early Zebrium customer who ran a POC with Zebrium's service, automating and identifying root cause problems within four very well established and well-known Cisco product lines including Webex client and UCS. I was pretty amazed at the results, and I think you'll be impressed as well. So thanks for being here. Let's get started with me right now is Larry Lancaster who's a founder and CTO of Zebrium, and he's joined by Rod Bagg who's a founder and Vice-President of Engineering at the company. Gents, welcome, thanks for coming on. >> Thanks. >> (indistinct). >> To be here. >> Great to be here. >> All right, Rod, talk to me. Talk to me about software downtime, what root cause means, all the buzzwords in your domain, MTTR and SLO, what do we need to know? >> Yeah, I mean, it's like you said. I mean, it's extremely important to our customers and to most businesses out there to drive up time and avoid as much downtime as possible. So, you know, when you think about it, all of these businesses, most companies nowadays, either their product is software and it's running, you know, running on the web, and that that's how you get a point click or their business depends on it and, you know, internal systems to drive their business and to run it. Now, when that is down, that is hugely impacting to them. So if you take a look, you know, way back, you know, 20, 30 years ago, software was simple. You know, there wasn't much to it. It was pretty monolithic, and maybe it took a couple of people to maintain it and keep it running. It wasn't really anything complicated about it. It was a single tenant piece of software. Today's software is so complicated, often running, you know, maybe hundreds of services to keep that or to actually implement what that software is doing. So as you point out, you know, enter the sort of observability space and the tools that are now in use to help monitor that software and make sure when something goes wrong, they know about it, but there's kind of an interesting stat around the observability space. So when you look at observability in the context or through the lens of the cost of downtime, it's really interesting. So observability tools are about a $20 billion market, okay? But the cost of downtime, even with that in place, is still hundreds of billions of dollars. So you're not taking much of a bite out of what the real problem is. You have to solve root cause and get to that fast. So it's all great to know that something went wrong, but you got to know why, and it it's our contention here that, you know, really, when you take a look at the observability space, you have metrics. That's a great tool. I mean, there's lots of great tools out there, you know, around metrics monitoring that's going to tell you when something went wrong. It's very rarely it's going to tell you why. Similarly for tracing, it's going to point you to where the issue is. It's going to take you through that stack and probably pinpoint where you're being, you know, where it's happening or where something is running slow potentially. So that's great, but again, the root cause of why it's happening is going to be buried in log files, and I can expand on that a little bit more, but, you know, when you're a software developer, and you're writing your software, those log files are a wealth of information. It's just a set of breadcrumbs that are littered with facts about how the software is behaving and why it's doing what it's doing or why it went wrong, and it's that that really gets you to the root cause very fast, and that's, our contention is that these software systems are so complex nowadays, and that the root cause is lying in those logs. So how do you get there fast? You know, we would contend that you better automate that or you're just doomed for failure, and that's where we come in. >> Great. >> Getting to that request. >> Thank you, Rod. You know, it's interesting. You talk about the $20 billion market. There's an analogy with security, right? We spend 80, $100 billion a year on securing our infrastructure, and yet we lose, probably, closer to a trillion dollars a year in breaches, and there's a similar analogy here. 20 billion could be 5x in downtime impacts or more. Okay, let's go to Larry. Tell us a little bit more about Zebrium. I'm interested always to ask a founder why you started the company. Rod touched on that a little bit. You guys have invented this concept of RCAs. What does it mean? What problems does it solve? And how does it solve the problem? Let's get into it. >> Yeah, hey, thanks, Dave. So I think when you said, you know, who's automating the observer? That's a great way to think about it because what observability really means is it's a property of a system that means you can see into it. You can observe the internal state, and that makes it easier to troubleshoot, right? But the problem is if it's too complicated, you just push the bottleneck up to your eyeball. There's only so much a person can filter through manually, right? And I love the way you put that. So that's a great way to think about it is automating the observer. Now, of course, it means that, you know, you reduce your MTTR, you meet your service level objectives, all that stuff, you improve customer experience, that's all true, but it's important to step back and realize like we have cracked a real nut here. People have been trying to figure out how to automate this part of sort of the troubleshooting experience, this human part of finding the root cause indicators for a long time, and until Zebrium came along, I would argue no one's really done it right. So, you know, I think it's also important, you know, as we step back, we can probably look forward five to 10 years and say, "Everyone's going to look back and say, 'How did we do all this manually?'" You're going to see this sort of last mile of observability and troubleshooting is going to be automated everywhere because otherwise, you know, people are just, they're not going to be able to scale their business. So, you know, I think one more thing that's important to point out is, you know, I think Zebrium, you know, it's one thing to have the technology, but we've learned we need to deliver it right where people are today. You can't just expect people to dive into a new tool. So, you know, we're looking at, you know, if you look at Zebrium, you'll put us on your dashboard, and we don't care what kind of a dashboard it is. It could be, you know, Datadog, New Relic, Elastic, Dynatrace, Grafana, AppDynamics, ScienceLogic, we don't care. You know, they're all our friends. So we're more interested in getting to that root cause than trying to fight, you know, these incumbents and all that stuff, yeah. >> Yeah, so interesting. Again, another analogy I think about, you know, you talked about automation, where to look back, and say, "This is what- We're never going to do this again." It's like provisioning LANs. Nobody provisioned LANs anymore. It's all automated. >> That's correct. >> So, Larry, stay with you. The skeptic in me says, "This sounds amazing," but if, you know, it probably too good to be true. Tell us how it works. >> Yeah, so that's interesting. So Cisco came along and they were equally skeptical. So what they did was they took a couple of months, and they did a very detailed study, and they got together 192 incidents across four product lines where they knew that the root cause was in the logs, and they knew what that root cause was because they'd had their best engineers, you know, work on those cases and take detailed notes of the incidents that had taken place, and so they ran that data through the Zebrium software, and what they found was that in more than 95% of those incidents, Zebrium reflected the correct root cause indicators at the correct time. Like that blew us away. When we saw that kind of evidence, Dave, I have to tell you, everyone was just jumping up and down. It was like, you know, it was like the Apollo Command Center, you know, when they finally, (Dave laughs) you know, touchdown on the moon kind of thing. So, you know, it's really exciting at a point in time to be at the company, like just seeing everything finally being proven out according to this vision. I'm going to tell you one more story, which is actually one of my favorites, because we got a chance to work with Seagate Lyve Cloud. So they're, you know, a hyper modern, you know, SaaS business. They're an S3 competitor. Zoom has their files stored on Lyve Cloud to give, you know, to let you know who they are. So, essentially, what happened was they were in alpha, in their early access, and they had an outage, and it was pretty bad. I mean, it went on for longer than a day, actually, before they were completely restored, and it was, you know, fortunately, for them, it was early access. So no one was expecting, you know, uptime, you know, service level objectives and so on, but they were scared because they realized if something like this happens in production, you know, they're screwed. So what they did was they saw Zebrium, they did some research, they saw Zebrium. They went in a staging environment, recreated the exact (indistinct) that they'd had, and what they saw was, immediately, Zebrium pops up a root cause report that tells them exactly the root cause that they took over a day to find. These are the kind of stories that let us know we're onto something transformational. >> Yeah, that's great. I mean, you guys are jumping up and down. I'm sure, we're going to hear from Cisco later. I bet you, they were jumping up and down, too, 'cause they didn't have to do all that heavy lifting anymore. So Rod, Larry's just sort of implying that or, actually, you guys both talked about that your tool's agnostic. So how does one actually use the service? How do I deploy it? >> Yeah, so let me step back. So when we talk about logs, right? Like, you know, all these red crumbs being in logs and everything else. So, you know, they are a great wealth of, you know, information, but people hate dealing with them. I mean, they hate having to go in and figure out what log to look at. In fact, you know, we had one of our, or we've heard from several of our customers now prior to using Zebrium, but when they're, you know, have some issue, and they know there's something wrong, something on their dashboard has told them that something's wrong, maybe a metrics is, you know, taken a blip or something's happened that they know there's a problem, we've heard from them that it can take like a number of hours just to get to the right set of logs, like figuring out over these hundreds of services where the logs are to get to them, maybe searching in a log manager, just to get into the right context even can take hours. So, you know, that's obviously the problem we solve, but, you know, we don't want them just looking at logs. I mean, you know, we don't want to put 'em back in the thing they don't like doing 'cause people don't do what they don't like doing. So we put it up on the dashboard. So if something is going wrong with your metrics, and that's the indicator or maybe it's something with tracing that you're sort of digging through now that you know something's wrong, we will be right on that same dashboard. So we're deployed as a SaaS service. You send us your logs. You click on one of our integrations, and we integrate with all these tools that Larry's talked about, and when we detect anything that is a root cause report, it will show up on your dashboard in the same timeline as those blips in your metrics. So when you see something going wrong, and you know there's an issue, take a look at the portion of your dashboard that is us, and we're going to tell you why. We're going to get you to the why that went wrong. Not no other work could be- You can, you know, also click down and click through to us so that you land up in our portal if you want to do some more digging around if you need to or whatever, maybe to get some context, what have you, but it's fair that you ever need to do that. The answer should be right there on your dashboard, and that's how we expect people to use it. We don't want them digging in logs and going through things. We want it to be right in their workflow. >> Great, thank you, Larry. So Rod, we talked about Cisco. We're going to hear more from them in a moment and Seagate. I would think this is like a perfect solution for a SaaS provider, anybody doing AIOps, do you have some examples of those types of firms leaning into this? >> Yeah, a couple of great, well, I mean, we got many of them, but couple that I'll touch on. We have an actual AIOps company that was looking for, you know, sort of some complimentary technology and so on, and so they decided to just put us through our paces by having one of their own SREs sign up for our service in our SaaS environment and send the logs from their system to us, you know, and just see how we did. So it turned out we ended up talking back to this SRE like a week after he had installed the product, you know, signed up, and then, you know, started sending us logs, and, you know, he was hemming and hawing saying that he was busy like, you know, like every SRE is, and that he didn't have a chance to really do much with us yet, and, you know, we just, you know, having this conversation on the phone, and he comes to tell us that, "Yeah, I've been busy because we had this, you know, terrible outage like, you know, five days ago," and we said like, "Okay, did you actually look on the Zebrium dashboard?" (laughs) And he goes, "You know what? I didn't even think to do it yet. I mean, I'd just been so busy and frazzled." So we have an integration with that company. He hadn't put that integration in so it wasn't in his dashboard yet, but it was certainly on ours. So he went there and he looks on the day like, you know, on the time range of when he had this incident, and right at the very top of the page on our portal was the incident with the root cause, and he was flabbergasted. It literally would've saved him hours and hours and hours. They had this issue going on for over 24 hours, and we had the answer right there in five minutes, and it was crazy, and we get that kind of story. It's just like the Seagate one. If you use us and you have a problem, we're going to detect it, and you're going to hear from Cisco how successful we are at detecting things. I mean, it'll be there when you have a problem. In SaaS companies, you know, one of our customers is Archera. They do cost optimizations for cloud properties, you know, for AWS optimization, Google cloud, and so on, but they use our software, and they have a lot of interaction, obviously, with these cloud vendors and the APIs of those cloud vendors. So, you know, in order to figure out you're costing at AWS, they're using all those APIs. So it turned out, you know, they had some issue where their services were breaking and we had that root cause report right on the screen, again, within five minutes that was pointing to an API problem with Google, and they had changed one of their APIs, and Archera was not aware of it. So their stuff was breaking because of a change downstream that we had caught, and I'll just tell you one last one because it's somewhat related to one of these cloud vendors of, you know, big cloud vendor who had an outage couple of months ago, and it's interesting because, you know, lot of our customers will set up shared Slack channels with us where we're monitoring or seeing their incidents as well as they are. So we get a little Slack representation of the incident that we detected for them or the root cause that we've detected for them, and that's in a shared community channel. So we could see this happening when that AWS outage happened. We could see our customers getting impacted by that AWS outage and the root cause of what was going on there in AWS that was impacting our customers, that was showing up in our incidents. Now, we didn't obviously, you know, have the very root cause of what was going on in AWS per se, but we were getting to the root cause of why our customer's applications were failing, and that was because of issues going on at AWS. >> Very interesting. I mean, I think one of your biggest challenge is going to be getting people's attention because these SREs is so busy, their hair's on fire. (all laughs) You know, he's like, "Hey, chap, I'm going to show you, look at this." >> I tell you. You get their attention, they love it. I mean, this AIOps company, I didn't even tell you the punchline there, but, you know, they had this incident that occurred that we found and, quite literally, the next week, they ended up signing up as a paid customer, so. >> That's great, and Larry, give you the last word. I mean, you know, Rod was talking about, you know, changes in APIs, and, you know, there's still a lot of scripts out there. You guys, if I understand it correctly, run both as a service in the cloud and you can run on-prem, which is important because there's a lot of sensitive information in logs and people don't want to leave. >> That's right, absolutely. >> But, yeah, close it out here. >> Yeah, I mean, you can, that's right, you can run it on-prem, just like we run it in our cloud. You can run it in your cloud or on your own infrastructure. Now, that's all true. You know, I think the one hurdle now that we have left as a company is getting the word out and getting people to believe that this is actually possible and try it for themselves. You don't believe it? Do a POC, try it yourself. And, you know, people have become so jaded by the lack of, you know, real sort of innovation in the software industry for the last 10 years that it's hard to get people to... But guys, you got to give it a shot. I'm telling you. I'm telling you right now, it works, and you'll hear more about that from one of our customers in a minute. >> Alright guys, thanks so much. Great story, really appreciate you sharing. >> Thank you. >> Yeah, thanks, Dave. Appreciate the time. >> Okay, in a moment, we're going to hear from Cisco who is the customer in this case example, and a company that is... Look, they have quite an impressive suite of observability tooling, and they've done a pretty compelling proof of concept with Zebrium using real data on some Cisco products that you've heard of like Webex. So stay tuned and learn about how you can really take advantage of this new technology called root cause as a service. You're watching "theCUBE", the leader in enterprise and emerging tech coverage. (bright outro music)

>>Okay, welcome back everyone to San Francisco, live coverage here with the cube 80, be summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the 80 us summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube, alumni and friend of the cube. I dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. I'm gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see. See you, sir. Chris pump. Cool. How are you? >>Good. How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes over the past couple years and your company raising some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so I, as the company started around four years back, I invested with a few of the investors and now I'm the CEO. Um, we have raised close to a hundred million there. The investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people all well known guys, Andy Beel chime Paul Mo Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take it the next stage? Well >>Of having you on the cube, Dave and I, David ante as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know who done? You >>Get the comment, this fun to talk to you though, you >>Get the commentary, you you're your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a 2 billion valuation back from the debt after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take? Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. Native NATO is a new buzzword and using the AI for customer service it operations. We talk about observability. I call it AI ops, applying ops for good old it operations management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events incidents. So I see a lot of work clicking for AIOps and AI service desk. What used to be help desk with ServiceNow BMC <inaudible> you see a new, a layer emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going off >>Is RPA a company is AI, is RPA a feed of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's a feature. >>It is very good point. Very, very good thing. So one is, it's the category for sure. Like it's a category, it's an area where RPA maybe change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be ed in every area. Yeah. Like we call cloud NATO and AI NATO. It'll become automation. NATO. Yeah. And that's your thinking? So >>It's most interesting me. I think about the, what you're talking about. What's coming to my is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software abstraction. Now you have all kinds of workflows abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So don't put the database became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you you're talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see it. MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall, got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative all the companies out here that we know. And we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the, to of the, in your mind, cuz you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to two things that I'm seeing out there. Remember days of Amazon created the startups 15 years back, everybody built on Amazon now Azure and GCP. The next layer would be is people don't just build on Amazon. They're going build it on top of snowflake. Companies are snowflake becomes the data platform, right? People will build on snowflake. Right? So I, my old boss Blankman trying to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud. Right's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldmans Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. He's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to everything on Amazon where possible whatever is, I cannot build, I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer. If I really need do size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll. >>So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It is, That's the application on another big CapEx ride, the CapEx of AWS or >>Cloud, and that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift, um, but snowflakes, a big customer and the they're probably paying AWS, I think bills too. So >>John video it's like whole Netflix is, and Amazon prime Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses, a data layer. So I think depending on the applic use case, you have to use each of the above. I think snowflake is here for a long term. So if I'm building an application, I want to use snowflake then, right. Think from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value. That's right. With some sort of internal hack. But I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening. Some point, when does the rising tide stop >>And >>The people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? >>I think it's growth. You call it cloud scale. You invented the word cloud scale. So I think, look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to text me or DMing next. Question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it >>Is. If I remember going back to our 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO, a line of business it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check our, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want get your reaction because I, I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or are um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona. You mentioned a AIOps we've been seeing AOPs IOPS blue booming and that's creating a new developer paradigm that's right. Which we call and coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this to engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same things? Do you agree? Um, do you disagree or can you share >>Yourself? I, no, I have a lot of thoughts that first is I see the AOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone through it. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to proactive solution with AOPs. But what you bring of a very good point on the data side, I think like we have a Amazon marketplace and for startup, there should be data exchange where you want to create for AOPs and AI service desk customers that give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make >>Them >>Better, make them better. Yeah. And I think there are a whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that data is very important. >>You've always been on, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is double, the >>Key cloud air kinda went private, so good stuff. But what are you working on right now? Give a, give a, um, plug for what you're working on. You'll still invest strength. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. >>So >>Right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers. Some of them you like it's zoom auto desk, MacAfee, uh, grantor. So all the top customers, um, mainly for it help desk customer service ops. Those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What what's their need? What category is it? >>I think the look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value. Prop. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the key. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at a summit in San, uh, in New York in the summer. So look for that on this calendar, of course, go to Aish startups.com and mention that it's ay for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break.

More bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software and it starts with great technical founders with great products and great bottoms of emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart, but Myer of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies there's no, I mean, consumer is enterprise now, everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. <laugh> but remember, like right now there's also a tech and VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are, uh, may maybe students of history and have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely one web three. Yeah. >>But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east of Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, well, >>Let's get, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher, a direct sales force and SAS kind of crushed that now SAS is being redefined, right. So what is SAS is snowflake assassin or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data and you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of common across all successful startups and the overall adoption of technology. Um, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually like growth, right. They're one and the same. So sometimes people think the product, uh, is what is driving growth. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this, but maybe started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing. It's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the, and they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I have what been saying on the cube for probably about eight years now that we are gonna hit digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. You, we hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home group. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal it'll trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion yeah. Around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? Yeah. It's so it's something that people just believe to be true almost without, uh, necessarily caring >>About data. Data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of it's about believing in the person. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. >>Oh, AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur. Right. And the persona of the entrepreneur would be, you know, so somebody who was a great salesperson or somebody who tell a great story, and I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it gonna it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in the new economy that we live in, really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative of because their product begins exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Speak to the user, but let me ask a question now that for the people watching, who are maybe entrepreneurial entre, preneurs, um, masterclass here in session. So I have to ask you, do you prefer, um, an entrepreneur come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine with you an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do, do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way. And we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be the, of more likely somebody is gonna align with your vision and, and wanna invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta >>Show the >>Path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle. The journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living, we'll say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. <laugh> so you, you know, you sort of have to balance the, you know, we, we know that the world is going in this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but some times it happens in six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Bel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There's three big trends that we invest in. And the they're the only things we do day in, day out one is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen, an alwa timeline >>Happening forever. >>But, uh, it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need you do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cybersecurity as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is run $150 billion. And it still is a fraction of what we're, >>What we're and national security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital that's >>Right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters, your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cuban. Uh, absolutely not. Certainly EU maybe even north Americans in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Guess be VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After this short break, stay with us. Everyone. Welcome to the cue here. Live in San Francisco. K warn you for AWS summit 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here, Justin Kobe owner, and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to mid-size businesses that are moving to the cloud, or have already moved to the cloud and really trying to understand how to best control security, compliance, all the good stuff that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas, up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by a of us. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization, but obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small mids to size business. They're all trying to understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're of like, listen, we gotta move to the cloud or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then so, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to mid-size businesses who don't have the technology talent on staff to be able to do >>That. Yeah. And they want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is not it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem. And you guys solve >>In the SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and our hardened solutions. And so, um, what we try to do with, to technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to yeah. Feel like, listen, at the end of the day, I'm gonna be spending money in one place or another, whether that's on primer in the cloud, I just want know that I'm doing that way. That helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early, not worrying about it, you got it mean most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. >>Yeah. Frog and boiling water, as we used to say, oh, it's a great analogy. So I mean, this, this is a dynamic. That's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam? You know, the 5,000 announcement or whatever. They did huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>Values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a 10 a company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back and we're the safety net. So when a customer is saying, right, I'm gonna spend a couple thousand and dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say your high profile and you're gonna potentially be more vulnerable to security attacks. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a four, >>The training alone would be insane. A risk factor. I mean the cost. Yes, absolutely opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018. When, uh, when we, he made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious, it wasn't requirement. It still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front >>Desk and she could be running the Kubernetes clusters. I >>Love it. It's >>Amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people with. And that's a cultural factor that you guys have. So, so again, this is back to my whole point out SMBs and businesses in general, small and large it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the buildout, um, uh, return factor, ROI piece. At what point in time as an owner, SMB, do I get to ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. >>This is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, >>That's, that's what, at least a million in loading, if not three or more Just to get that app going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side. No. And they remind AI and ML. >>That's right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>So like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like it, >>But that's so true. I mean, when I think about how, if I was a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. It's something that we talk about every, with every one of our small to mid-size >>Businesses. So just, I want get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduced other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. Yeah. I came in, I did an internship for six months and I loved it. I learned more in those six months than I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2000 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner. But if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy the business with me. >>And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like, if we're own, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015 and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the BI cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us. And we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business to migrate completely to the cloud is as infrastructure was considered, that just didn't happen as often. Um, what we were seeing where the, a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plugin for the company. Awesome. >>So, uh, there's no question. Every customer is looking migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating into the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customer is not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so they can modernize. So >>Like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable win that's right. Seeing the value and ING down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate >>It. Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break >>Live on the floor in San Francisco for Aus summit. I'm John for host of the cube here for the next two days, getting all the actual back in person we're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be here. >>So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to be back through events. It's >>Amazing. This is the first, uh, summit I've been to, to in what two, three >>Years. That's awesome. We'll be at the, uh, a AWS summit in New York as well. A lot of developers and the big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything devs sec ops, everyone kind of sees that you got containers, you got Benet, he's got cloud native. So the, the game is pretty much laid out. Mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's >>Right. Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions. The at our around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running or FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam slaps in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listens to the customer. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. >>It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data in is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always use the riff on the cube, uh, cause it's basically Amazon in a box, pushed in the data center, running native, all this stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard. Deepak syncs group is doing some amazing work with opensource Raul's team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my datas center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone now happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware can go deploy EKS anywhere in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative. Does that get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is that they don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on what's making them money as a business. They wanna focus on their applications. They wanna focus on their customers. So they look towards AWS cloud and a AWS. You take the infrastructure, you take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it >>Works? Right. And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy fin in the Caribbean, we're gonna talk about hurricanes. And we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data and you have applications that are tapping into that, that requirement. It makes total sense. We're seeing that across the board. So it's not like it's a, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on >>It's interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, project going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain just for like smart contracts, for instance, or certain transactions. And they go to Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service. Well, what happened to decentralized? >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a, I also want all the benefit of the cloud. So I want the modern, and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. >>Yeah. Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment that, that manufacturing plant can be hooked up, they don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with a regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Inside of that manufacturing plant, we can do pre-procesing on things coming out of the robotics, depending on what we're manufacturing. Right. And then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data, data lake, or whatever, >>To the data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just time manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yeah. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Right. And then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are, and we have more and more people that, that want to talk less about databases and want to talk about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data. Uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session this, but the one pattern we're seeing come of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes co as we call it in our last showcase, we did a whole whole an event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are running petabyte level. Um, they're, they're essentially data factories on, on, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a, kind of a, um, fun, I was told to ask you about your personal background on premise architect, Aus cloud, and skydiving instructor. How does that all work together? What tell, what does this mean? >>Yeah. Uh, I, >>You jumped out a plane and got a job. You got a customer to jump >>Out kind of. So I was, you jumped out. I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and how his customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, I started in the first day there, we had a, and, uh, EC two had just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to premises. >>So it's such a great story. You know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people, right. Yeah. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting stuff like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here, lot in San Francisco for AWS summit, I'm John for your host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look at this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube, a summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the, a us summit in New York city this summer, check us out then. But right now, two days in San Francisco getting all coverage, what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, Pam. Cool. How are you? Good. >>How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah so give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people, all known guys that Antibe chime Paul Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved. >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? Well, >>I love having you on the cube, Dave and I, and Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh>, >>You know, >>You >>Get, the comment is fun to talk to you though. >>You get the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud out scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on our $2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded observability there's 10 million observability companies. Data is the key. This is what's your angle on this. What's your take. Yeah, >>No, look, I think I'll give you the view that I see, right? I, from my side, obviously data is very clear. So the things that room system of record that you and me talked about, the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA NA is a new buzzword and using the AI for customer service, it operations. You talk about observability. I call it AI ops, applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI service desk. What needs to be helped desk with ServiceNow BMC <inaudible> you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, or is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. >>It's a feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be a, in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kind having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software was action. Now you have all kinds of workflows abstractions everywhere. Right? So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become all polyglot databases. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area, like, as you were talking about, it should be part of ServiceNow. It should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies could cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also will have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall. You got, um, we're back to vents, but you got, you know, am Clume Ove, uh, Dynatrace data dog, innovative all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders, how Amazon created the startups 15 years back, everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're gonna build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis of a couple months ago called castles in the cloud where your Mo is what you do in the cloud. Not necessarily in, in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage, and guys, Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get it. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Now. They say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. It >>Is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer if I really need to size build it on force.com Salesforce. Yeah. Right. So I think that's where you'll see. So >>Basically the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift. Um, but Snowflake's a big customer in the, they're probably paying AWS, I think big bills too. So >>Joe on very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses or data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose, your, you that's right with some sort of internal hack. Uh, but I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and do the people shopping up their knives, it gets more competitive or is it just an infinite growth? So >>I think it's growth. You call it cloud scale, you invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the more market, feel free to text me or DMing. The next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't get your thoughts on that? What, >>No, it is. If I growing by or 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO or line of business, it's gone. Yeah. Can it go more? I think it can in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure is code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself a lot of first is I see the AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution. We will go future towards predict to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service desk. Customers are give the data, share the data because we thought the data algorithms are useless. I can them, but I gotta train them, modify them, tweak them, make them >>Better, >>Make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data Rick has grown. >>It is. They doubled the >>Key cloud air kinda went private. So good stuff, man. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk McAfee, uh, grand to so all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict is one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's decipher all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're can see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with bill group. He's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank >>You. Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit hosting, but they don't know how to do it. Like they're not >>Doing it right? So there's something opportunity there. It's like here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a midsize island, do begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enter prize technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's of all the Adams, especially new CEO. Andy's move on to be the chief of all Amazon. Just so I'm the cover of was it time met magazine? Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to port eight of us is trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. <laugh> either way, sounds like more exciting. Like I better >>Have a replacement ready <laugh> I, in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in east sports with other people in pure simulation of the race car. You gotta get the latest and videographic card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter, check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late? Has there been uptick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do >>That. We should do that. Actually. I think you're people would call in, oh, >>I, I think >>I guarantee we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised about anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the >>Customer. You know, I always joke with Dave Alane about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't call, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented SU sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting. So they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination >>Of gots. You got EMR, you got EC two, you got S3 SQS. Well, RedShift's not an acronym you >>Gets is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, they >>Shook up bean stock or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, well, we built this thing in 2005 and everyone hates it, but while we certainly can't change it, now it has three customers on it. John three <laugh>. Okay. Simple BV still haunts our dreams. >>I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm I couldn't figure out. Why can you just like roll it over? Why, why are you telling me? Just like, give me something else. All right. Okay. So let me talk about, uh, the other things I want to ask you, is that like, okay. So as Amazon better in some areas where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So Redshift, snowflake data breach is out there. So you got this co-op petition. Yes. How's that going? And what do you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with, and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multicloud. Cause obviously the other cloud shows are coming up. Amazon hated that word multicloud. Um, a lot of people though saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Cloudant loves that term. Yeah. >>You know, you're building in multiple single points of failure, do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about my multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on, but my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah, course. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journeyman and the, and the cloud journey going to all the events and then the pandemic hit. We now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing or just big changes you've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck build group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is evenly. Distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smelled delightful. Let me assure you. But it was, but it's also nice to be. >>I have a product for you if you want, you know? Oh, >>Oh excellent. I look forward to it. What is it? Pudding? Why not? <laugh> >>What else have you seen? So when accessibility for talent. Yes. Which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentation have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. Yeah. >>And you turn off your iMessage too. >>Oh yes. It's always fun in the, in the meetings when you're ho to someone and their colleague is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. Why >>Not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't the only entire sure. It's >>Fine. My kids text. Yeah, it's fine. Again, that's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you or I want to put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Yeah. Tell me a story there. >>I, I think >>That gets a glimpse in a hook and makes >>More, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did a thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they call for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in pan or Singapore, uh, to access them. And now they're in the index, they're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content. >>Absolutely >>Content value plus and >>Effecting. And that is the next big revelation of this industry is going to realize you have different companies. And, and I Amazon's case different service teams all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna basically give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here at Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up from the beginning. His great guy, check out his blog, his site, his newsletter screaming podcast. Corey, final question for, uh, what are you here doing? What's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck bill group. We solved one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I in my continual and ongoing love affair with the sound of my own voice. >><laugh> and you're good. It's good content it's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No >>Thank you button. >>You. Okay. This the cube covers here in San Francisco, California, the cube is back going to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John fur. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS two great guests here from the APN global APN Sege chef Jenko and Jeff Grimes partner lead Jeff and Sege is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS. We'll start >>Program. That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, >>Of course. >>Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously we're in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. A lot of 'em getting funded, big growth and cloud big growth and data secure hot in all sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to pro vibe white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support. Dedicat at headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, AWS startup, AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall effort for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, you got a >>Lot. We've got a lot. >>There's a lot. I gotta, I gotta ask a tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it for what do I get out of it? What's >>A story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company, right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here a lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. So, um, I think what's been fun over the years for me personally, I came from a startup brand sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise is sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. But still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters. Right. Where ever everyone's going after similar things. >>Yeah. And I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, you guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake that built on top of AWS. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's all the foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competencies, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching, certainly I asked this a lot. There's a lot of companies startups out there who makes the cut, is there a criteria cut? It's not like it's sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How, how do you guys focus? How do you guys focus? I mean, you got a good question, you know, thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really, we're trying to find these ISVs that can solve, uh, really interesting AWS customer. >>You guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line, business line business, like web >>Marketing, business apps, >>Owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage back up ransomware kind of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startups that we cover is that they've got, they truly have support from a build market sell perspective, right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can wish that sock report, oh, download it on the console, which we use all the time. <laugh> exactly. But security's a big deal. I mean, you know, ask the res are evolving, that role of DevOps is taking on dev SecOps. Um, I, I can see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or that not part of, uh, uh, >>Yeah, >>So the partner development manager can be an escalation for absolutely. Think of that. 'em as an extension of your business inside of AWS. >>Great. And you guys, how is that partner managers, uh, measure >>On those three pillars? Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's very, >>I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top line. >>Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the star ups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition. The, at the big guys have mm-hmm <affirmative>. And so that's, our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF. And then outside of SF, you guys have a global pro, have you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here. That's doing, uh, a AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with a AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously see a ton of partners from the bay area that we support. Um, but we're seeing a lot of really interesting technology come out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy and real quick before you get into surge. It's interesting. The VC market in, in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. Let's see if they crash, you know, but we don't see that happening. I mean, people have been predicting a crash now in, in the startup ecosystem for least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the demo because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Celski both say the same thing during the pandemic. Necessity's the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of what me through. Pretend me, I'm a start up. Hey, I'm on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Search? What, what do >>I do? That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement? Where do they want to go at the end of the day? Um, and oftentimes because we've worked with, so how many successful startups that have come out of our program, we have, um, either through intuition or a playbook determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time. Yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love startups here in the cube because one, um, they have good stories, they're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they, they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startups. Showcases startups.com. Check out AWS startups.com and she got the showcase. So is, uh, final word. I'll give you guys the last word. What's the bottom line bumper sticker for AP globe. The global APN program summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally. We'll start >>With you. Yeah. I think the AWS global startup programs here to help companies truly accelerate their business full stop. Right. And that's what we're here for. Love it. >>It's a good way to, it's a good way to put it. Dato yeah. >>All right. Thanks for coming out. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. I'll making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for >>Watching Cisco, John. >>Hello and welcome back to the Cube's live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city coming up this summer will be there as well. Events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net. Check it out a lot of content this year more than ever a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability, Jeremy. Great to see you. Thanks. >>Coming on. Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability Smith hot area, but also you've been a senior executive president of Dell EMC. Um, 11 years ago you had a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here, you predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for sort of catching that bus early, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply snowflake, obviously you involved, uh, at the board level, the other found, you know, the people there, uh, cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applications. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflakes is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think right in more software than, than ever before are why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now, back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data. And the, you know, there's sort of the transactions, you know, what you bought today are something like that. But then there's what we do, which is all the telemetry, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then why not? Where did they drop off all of that? They wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code one of the insights that we got out of that, and I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data, cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and yeah, >>Yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that. Yeah, it is about the data. You know, if I can better understand my data better than my competitor, then I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. >>So let's talk about observing you the CEO of, okay. Given you've seen the ways before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of something from years gone by. >>Um, there's a guy called, um, Rudy Coleman in 1960s coiner term and, and, and the term was being able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of four years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. Um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike and our board. And, um, you know, part of the observed story is closely knit with snowflake all of that time with your data, you know, we, we store in there. >>So I want to get, uh, yeah. Pivot to that. Mike SP snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became. Yeah. Snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you, you're doing some stuff with snowflake. So as a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? I mean, >>Having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, 20 years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah, >>It's okay. Columbia, but hyperscale. Yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job are doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy, >>Happy. So you're building on top of snowflake, >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You're >>Still on the board. >>Yeah. I'm still on the board. Yeah. That's a risk I'm prepared to take. I am more on snowing. >>It sounds well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No, yeah. Serious one. But the, this is a real dynamic. It is. It's not a one off its >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is in order of magnitude, more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I've believe the opportunity for folks like snowflake and, and folks like observe it. It's an order of magnitude more than it was for the Oracle and the SAPs of the old world. >>Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite easy >>Or be the platform, but it's hard. There's only like how seats were at that table left >>Well value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, rack space and there's 1,000,001 infrastructure, a service platform as a service. My, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. Don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters within if the provision, the CapEx. Yeah. Now the CapEx is in the cloud. Then you build on, on top of that, you got snowflake. Now you got on top of that. >>The assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's almost free, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get >>Into. And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a series us multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me, uh, like, look you build in on snowflake. Um, you, you know, you, you, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying their money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well and observe, but then I've got half the development team working on something that will never be as good as snowflake. And so we made the call early on that. No, no, we, we want a eight above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's obviously a more on snowflake. I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS. >>Well, and for snowflake and, and any platform from VI, it's a beautiful thing because, you know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of >>Ecosystems. Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New product, you're scaling a step function with them. >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is inve >>You know, well, Jeremy great conversation. Thanks for sharing your insights on the industry. Uh, we got a couple minutes left, um, put a plug in for observe. What do you guys know? You got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting in traction. >>Yeah. Yeah. Scales >>Around the corner. Sounds like, are you, is that where you are scale? >>We've got a big that that's when coming up in two or three weeks, we've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, but it's gonna be exciting. And, and like I said, so hill continue to, to, >>I think capital one's a big snowflake customer as well. Right. >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. And, and today that, that is one of Snowflake's biggest accounts, >>Capital, one, very innovative cloud, obviously Atos customer, and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, >>Right? >>So you got POCs, what's that trajectory look like? Can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit this straight and narrow and, and gas it fast. >>Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage. His questions that the board are always about, like is the product, right? Is the product right? Is the product right? Have you got the product right? And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we we're, we're adding all the tracing visualizations. So people will be able to the kind of things that by in the day you could do with the new relics and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one, cuz we sort of complete the trifecta, you know, the, the >>Logs, what's the secret sauce observe. What if you had the, put it into a, a, a sentence what's the secret sauce? >>I, I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors and, and the biggest thing our investors give is it actually, it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. While I got you here, you've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their, this restructure. So, so a lot of happening in cloud, what's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B it prepared to take risks and it's, it's a race against time to you'll get their, their offerings in this, a new digital footprint. >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. Yeah, >>Better. It's an amazing story. I mean, you know, we're, we're on AWS as well. And so I, I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late nineties, it was, they stopped, uh, really caring about developers in the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing headstart and if they did more, you know, if they do more than that, that's, what's gonna keep this juggernaut rolling for many years to come. >>Yeah. They got the Silicon and got the stack. They're developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great startup. Thanks for coming on the cube. Always a pleasure. Okay. Live from San Francisco. It's to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers are the bay air at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics, AI. They all coming together. Lots of coverage stay with us today. We've got a great guest from Bel VC. John founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, man. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over decade. Um, >>It's been at least 10 years, >>At least 10 years more. And we don't wanna actually go back as bring back the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in a second. We, >>We are, it's a little bit of a throwback to the path though, in my opinion, >>It's all the same. It's all distributed computing and software. We ran each other in cube con. You're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software to take an old something old and make it better new, faster. So tell us about Bel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you, I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called IM logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of software companies, uh, early investor in open source companies and cloud companies and spent a really wonderful years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start an enterprise software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchase software that is traditionally bought and sold tops down. But you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great bottoms of motions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background. You're super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is, is all companies there's no, I mean, consumer is enterprise now. Everything is what was once a niche, not, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, well, >>MFTs is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are of may, maybe students of his stream have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely web >>Three. Yeah. But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case and maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30 a year. So it it's a, it's a just incredibly fast >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Lutman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, hire a direct sales force and sass kind of crushed that now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, and they own all my data. And you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all six of startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement may be started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the offic and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been saying on the cube for probably about eight years now that we are gonna hit a digital hippie Revolut, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one of group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on like, well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source. One example of that religion. Some people say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean, >>The data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the first. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. And I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it's gonna, it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy, that're, we live in really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their product begin for exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with for right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Exactly. Speak to the user. But let me ask a question now that for the people watching, who are maybe entrepreneurial entre entrepreneurs, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think will become, right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna to align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta show the path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the, the latest trends because it's over before you even get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens ins six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Tebel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There there's three big trends that we invest in. And then the, the only things we do day in day out one is the explosion at open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen an alwa timeline happening forever, but it is, it is accelerating faster than we've ever seen. So I, I think it's its one big mass of wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole like economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion and it still is a fraction of what >>We're, what we're and even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right. Arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say you gotta love your firm. Love who you're doing. We're big supporters of your mission. Congrat is on your entrepreneurial venture. And uh, we'll be, we'll be talking and maybe see a Cuban. Uh, >>Absolutely >>Not. Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Des bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California, after the short break, stay with us. Hey everyone. Welcome to the cue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here. Justin Colby, owner and CEO of innovative solutions they booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. Yeah. >><laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving to the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is. But now we have offices down in Austin, Texas up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? Yeah. >>It's a great question. Every CEO I talk to, that's a small to mid-size business. I'll try and understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the out or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>The SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has additional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start the, on your journey in one way, and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early and not worrying about it, you got it. I mean, most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say so, oh, it's a great analogy. So I mean this, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talk to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam, you know, five, a thousand announcement or whatever they did with huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just product. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>The values. >>Our mission is, is very simple. We want to help every small to mid-size business, leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the pro of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning know that we have their back and we're the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going on loan. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own, it would cost 'em a fortune. If >>It's training alone would be insane. A risk factor not mean the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I >>Love it. It's amazing. So I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get the right >>People involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and BIS is in general, small and large. It staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the why? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side now. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>Like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like >>It, >>But that's so true. I mean, when I think about how, if I were a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we tell, talk about every, with every one of our small to mid-size >>Businesses. So just, I wanna get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, on the value of this business and who knows where you guys are gonna be another five years, what do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy into the business with me. >>And they were the owners, no outside capital, none >>Zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons, they all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an early now process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting going all in on the cloud was important for us and we haven't looked back. >>And at that time the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly. And those kinds of big enterprises, the GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to mid-size business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing where a lot of our small to mid-size as customers, they wanted to leverage cloud-based backup or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is it the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strap and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and Ling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. >>Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break, >>Live on the floor and see San Francisco for a AWS summit. I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at a AWS reinvent a few months ago. Now we're back. Events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube. Check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be >>Here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the UHS summit in New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the game is pretty much laid out mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give an example, uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, it's interesting, Matthew is that we've been covering a, since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam's in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listen to the customers. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does computing. It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue at the edge what's driving the behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see that the data at the edge, you got 5g having. So it's pretty obvious, but there's a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation where today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube cause it's basically Amazon and a box pushed in the data center, running native, all the stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard Deepak syncs. Group's doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW, he was giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outposts. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere or in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative as that you get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are, they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They want on their applications. They want to focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping of these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we talk about hurricanes and we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where you now have data and you have applications that are tapping into that, that required. It makes total sense. We're seeing that across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming a, uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart concept. We use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decentralized. >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my ad. And I also want all the benefit of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercial available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-procesing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard for >>Data, data lake, or whatever, to >>The data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data, unless you have to, um, those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? This is a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud out? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe maybe decision can wait. Right? Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot too, doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And >>Well, I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern was income of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes code, as we call it our lab showcase, we did a whole, whole, that event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are run petabyte level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background on premise architect, a cloud and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You, you got a customer to jump out >>Kind of. So I was jump, I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Yeah. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his cus customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods teaching scout. I think I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started in the first day there, uh, we had a, a discussion, uh, EC two, just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that and through being an on premises migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to >>It's. So it's such a great story, you know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early day was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, um, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days, AWS, the same feeling we have when we >>It's pretty much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live and San Francisco for summit. I'm John Forry host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. look@thiscalendarforallthecubeactionatthecube.net. We'll be right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host to the cube. We'll be at the eight of his summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dudes, car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, sir. Chris. Cool. How are, are you >>Good? How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me back to be business with you. Never great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like Norwes Menlo, Tru ventures, coast, lo ventures, Ram Sheam and all those people, all well known guys. The Andy Beckel chime, Paul Mo uh, main web. So a whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it come? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? >>Well, I love having you on the cube, Dave and I, Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a GE, you're like a guest analyst. <laugh> >>You know who you >>Get to call this fun to talk. You though, >>You got the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about on cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing DACA just raised a hundred million on a 2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take. Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that remember system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud NA it'll be called AI, NA AI native is a new buzzword and using the AI customer service it operations. You talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and service desk. What needs to be helped us with ServiceNow BMC G you see a new ELA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflow, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with a AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's >>A feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company, or, but that automation should be embedded in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it. It was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all, all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become called poly databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you were talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you've got the expo hall. We got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Bel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation, clouds bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically data is everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're going to build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's in the of, <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of shit on us saying, Hey, you guys terrible, they didn't get it. Like, yeah. I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> if he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake. So can build it on snowflake. I can use them for data layer. If I really need to size, I'll build it on four.com Salesforce. So I think that's where you'll see. So >>Basically if you're an entrepreneur, the north star in terms of the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales? The snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got red, um, but Snowflake's a big customer. They're probably paying AWS think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouse as a data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value that's right. But some sort of internal hack, but I think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point. When does the rising tide stop >>And >>Do the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it cloud scale. You invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to, to XME or DMing. Next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and, you know, small, medium, large, and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or a growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it is. >>If I remember going back to our 2007 or eight, it, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO line business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there, um, and gives back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself? No, I have a lot of thoughts that plus I see AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution will go future towards to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers are give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to our big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is uh, double, the key >>Cloud kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk, Mac of fee, uh, grandchildren, all the top customers. Um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict S one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of 80 summit, 2022. And we're gonna be at 80 summit in San, uh, in New York and the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This to cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back a little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove, psyched to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube, a lot of hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with duck, bill groove, he founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe as shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at Mark's been doing a lot of shit posting lately, all a billionaires are shit posting, but they don't know how to do it. Like they're not >>Doing it right. Something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. This >>Shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on the other side, I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enterprise tech, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you can see the growth of cloud native Amazons, all, all the Adams let see new CEO, Andy move on to be the chief of all. Amazon just saw him. The cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything these folks do. They they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. It's, it's sprawling, immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. Well, >>There's a lot of force for good conversations, seeing a lot of that going on, Amazon's trying to port and he was trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, sounds like more exciting >>Replacement ready <laugh> in case something goes wrong. I, the track highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other, in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's back any blow back late there been uptick. What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, >>I think >>Chief, we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave ante about how John Fort's always at, uh, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0 5, or we can't, >>We have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting, they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on a number of words. They can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service, ridiculous name. They have systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's >>Fun. What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, Redshift the on an acronym, you >>Gots is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation. >>They still up bean stalk. Or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it. John three <laugh>. >>Okay. >>Simple BV still haunts our dreams. >>I, I actually got an email. I saw one of my, uh, servers, all these C two S were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, give me something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay. So as Amazon gets better in some areas, where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database, Snowflake's got a database service. So Redshift, snowflake database is, so you got this co-op petition. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want and they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word, like multi sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multi-cloud >>Multiple single points? >>Dave loves that term. Yeah. >>Yeah. You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, talk about other clouds, bad direction to go in from a market cap perspective, it doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing, because it solves problems. That's when I shut up and listen. Yeah. >>Cool. Awesome. Corey, I gotta ask you a question, cause I know you, we you've been, you know, fellow journeymen and the, and the cloud journey going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You got a pretty big community growing and it's throwing like crazy. What's the weirdest or coolest thing, or just big chain angels. You've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating. You're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, fun, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is even distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smell delightful. Let make assure you, but it was, but it's also nice to be. >>I have a product for you if you want, you know. >>Oh, excellent. I look forward to it. What is it putting? Why not? <laugh> >>What else have you seen? So when accessibility for talent, which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentations have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. >>Yeah. And also turn off your IMEs too. >>Oh yes. It's always fun in the, in the meetings when you're talking to someone and their co is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. >>Why not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't. No, the only encourager it's fine. >>My kids. Excellent. Yeah. That's fun again. That's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you, or I wanna put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Tell me a story there. >>I, I >>Think that gets a glimpse in a hook and >>Makes more, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did it thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they called for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in Japan or Singapore to access them. And now they're in the index. They're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content, >>Absolutely >>Content value plus >>The networking. And that is the next big revelation of this industry is going to realize you have different companies. And in Amazon's case, different service teams, all, all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here with Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up in the beginnings. Great guy. Check out his blog, his site, his newsletter screaming podcast. Cory, final question for you. Uh, what do you hear doing what's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck build group. We solve one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I indulge my continual and ongoing law of affair with the sound of my own voice. >><laugh> and you good. It's good content. It's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No, thank you. Fun. You. Okay. This the cube covers here in San Francisco, California, the cube is back at to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John furry. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS. The two great guests here from the APN global APN se Jenko and Jeff Grimes partner leader, Jeff and se is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS global startup program. >>That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, of course. Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously were in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. Lot of 'em getting funded, big growth and cloud big growth and data security, hot and sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support, dedicated headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, start AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall F for, for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, I got >>A lot. We've got a lot. >>There's a lot. I gotta, I gotta ask the tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it. What do I get out of it? What's >>A good story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company. Yeah. Right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. Sure. So, um, I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. Yeah. Still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters right. Where everyone's going after similar things. >>Yeah. I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, yeah. You guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake, they're built on top of AWS. Yeah. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps compet, the, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching. Certainly I asked this a lot. There's a lot of companies startups out there who makes the, is there a criteria? Oh God, it's not like his sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How do you guys focus? How do you guys focus? I mean, you got a good question, you know, a thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the fees that we look after our infrastructure ISVs, that's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve, uh, really interesting AWS customer challenges. >>So you guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line of business line, like web marketing >>Solutions, business apps, >>Business, this owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage, backup, ransomware of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startup that we cover is that they've got, they truly have support from a build market sell perspective. Right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can we waste that sock report? Oh, download it, the console, which we use all the time. Exactly. But security's a big deal. I mean, you know, SREs are evolving, that role of DevOps is taking on dev SecOps. Um, I, I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not, not part of a, uh, >>Yeah, >>So the partner development manager can be an escalation point. Absolutely. Think of them as an extension of your business inside of AWS. >>Great. And you guys how's that partner managers, uh, measure >>On those three pillars. Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's >>Very important. I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top >>Line. Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the startups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. Mm-hmm <affirmative> the challenge is they just might not have the brand recognition that the big guys have. And so that it's our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF and then outside SF, you guys have a global program, you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here that's doing, uh, AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously a ton of partners, I, from the bay area that we support. Um, but we're seeing a lot of really interesting technology coming out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy real quick, before you get in the surge. It's interesting. The VC market in, in Europe is hot. Yeah. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. We'll see if they crash, you know, but we don't see that happening. I mean, people have been projecting a crash now in, in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Leski both say the same thing during the pandemic necessity, the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of walk me through, pretend me I'm a startup. Hey, I am on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Surge? What, what do I do? >>That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement and where do they want to go at the end of the day? Um, and oftentimes because we've worked with so many successful startups, they have come out of our program. We have, um, either through intuition or a playbook, determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love star rights here in the cube because one, um, they have good stories. They're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startup showcases startups.com. Check out AWS startups.com and you got the showcases, uh, final. We I'll give you guys the last word. What's the bottom line bumper sticker for AP the global APN program. Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally start >>With you. Yeah. I think the AWS global startup program's here to help companies truly accelerate their business full stop. Right. And that's what we're here for. I love it. >>It's a good way to, it's a good way to put it Dito. >>Yeah. All right, sir. Thanks for coming on. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of the realities here. Open source and cloud all making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for watching >>John. >>Hello and welcome back to the cubes live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city. Coming up this summer, we'll be there as well at events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net, check it out a lot of content this year, more than ever, a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability Jeremy. Great to see you. Thanks >>Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability hot area, but also you've been a senior executive president of Dell, uh, EMC, uh, 11 years ago you had a, a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here. You predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for, for sort of catching that bus out, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved, uh, the board level, you know, the founders, you know, the people there cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applic. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflake is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think riding more software than, than ever fall. Why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data and the, you know, the sort of the transactions, you know, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then I not, where did they drop off all of that they wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code. One of the insights that we got out of that I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some query, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and >>Yeah, yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you, of enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I, I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that yeah, it is about the data. You know, if I can better understand my data better than my competitor than I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. So >>Let's talk about observing you the CEO of, okay. Given you've seen the wave before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of, of something from years gone by. >>But, um, there's a guy called, um, Rudy Coleman in 1960s, kinder term. And, and, and the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of the all years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. <affirmative> um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike on our board. And, um, you know, part of the observed story yeah. Is closely knit with snowflake because all of that time data know we, we still are in there. >>So I want to get, uh, >>Yeah. >>Pivot to that. Mike Pfizer, snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with snowflake. So a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? >>I mean, having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, to many years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operator and system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah. It's >>Okay. But hyperscale, yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generator data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snow snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy. >>So you're building on top of snowflake. >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You >>Still on the board. >>Yeah. I'm still on the board. Yeah. That that's a risk I'm prepared to take <laugh> I am long on snowflake you, >>Well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No know just doing, but the, this is a real dynamic. It is. It's not a one off it's. >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is an order of magnitude more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I believe the opportunity for folks like snowflake and folks like observe it's an order of magnitude more than it was for the Oracle and the SAPs of the old >>World. Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite >>Easy or be the platform, but it's hard. There's only like how many seats are at that table left. >>Well, value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, Rackspace and there's 1,000,001 infrastructure, a service platform as a service, my, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. You don't hear so much about it, these, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters. Cause then if the provision, the CapEx, now the CapEx is in the cloud. Then you build on top of that, you got snowflake you on top of that, the >>Assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's >>Almost free, >>But, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get into. >>And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a serious, multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me like, look, you're building on snowflake. Um, you, you know, you are, you are, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying them money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well in observe, but then I've got half the development team working on in that will never be as good as snowflake. And so we made the call early on that. No, no, we, we wanna innovate above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's actually more on snowflake. I I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS >>One and for snowflake and, and any platform provider, it's a beautiful thing. You know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of ecosystems. >>Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New products. You're scaling that function with the, >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is invaluable, >>You know, but Jeremy Greek conversation, thanks for sharing your insights on the industry. Uh, we got a couple minutes left. Um, put a plug in for observe. What do you guys, I know you got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting traction. Yeah. >>Yeah. >>Scales around the corner. Sounds like, are you, is that where you are scale? >>Got, we've got a big announcement coming up in two or weeks. We've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, uh, but it's gonna be exciting. And, and like I saids hill continued to, to, to stick, >>I think capital one's a big snowflake customer as well. Right. They, >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. Yeah. And, and today that, that is one of Snowflake's biggest accounts. >>So capital one, very innovative cloud, obviously AIOS customer and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, right? So you got POCs, what's that trick GE look like, can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit the straight and narrow and, and gas it >>Fast. Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage is questions that the board are always about, like, is the product, right? Is the product right? Is the product right? If you got the product right. And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we were, we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the new lakes and, and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us, this year's a big one, cuz we sort of complete the trifecta, you know, the, the logs, >>What's the secret sauce observe. What if you had the, put it into a, a sentence what's the secret sauce? I, >>I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors. And, and the biggest thing our investors give is actually it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. Why I got you here? You've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their business restructure. So a lot happening in cloud. What's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out out a way to take their, this to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B prepared to take risks and it's, it's a race against time to, you know, get their, their offerings in this. So a new digital footprint, >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10. Uh, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. >>Yeah. They're, they're, it's an amazing story. I mean, you know, we we're, we're on AWS as well. And so I, I think if they keep nurturing the builders in the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late it was, they stopped, uh, really caring about developers and the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing head start and if they did more, you know, if they do more than that, that's, what's gonna keep the jut rolling for many years to come. Yeah, >>They got the silicone and they got the staff act, developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great start. Thanks for coming on the cube. >>Always a pleasure. >>Okay. Live from San Francisco to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers of the bay area at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics AI thing, all coming together. Lots of coverage stay with us today. We've got a great guest from Deibel VC. John Skoda, founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, Matt. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over a decade. Um, >><affirmative>, it's been at least 10 years now, >>At least 10 years more. And we don't wanna actually go back as frees back, uh, the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in >>Second. We, we are, it's a little bit of a throwback to the path though, in my opinion, >><laugh>, it's all the same. It's all distributed computing and software. We ran each other in cube con you're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software is take old something old and make it better, new, faster. <laugh>. So tell us about Deibel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you're doing. I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called, I am logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of our companies, uh, early investor in open source companies and cloud companies and spent a really wonderful 12 years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start enter price software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting in an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building products that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchased software that has traditionally bought and sold tops down. But, you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early opts. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great and emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies. The is no, I mean, consumer is enterprise. Now everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. Well, and, >>And I think all of us here that are, uh, maybe students of history and have been involved in, open in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three movement. >>The hype is definitely that three. >>Yeah. But, but >>You know, for >>Sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many men over, uh, 500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant, but it's also the hype of like the web three, for instance. But you know, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher direct sales force and SAS kind of crushed the, at now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data. You know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all successful startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. You >>Just pull the >>Product through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement maybe started with open source where users were, are contributors, you know, contributors, we're users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a GenXer technically, so for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been staying on the cube for probably about eight years now that we are gonna hit a digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>It's the main for days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean >>The decision making, let me ask you this next question. As a VC. Now you look at pitch, well, you've made a VC for many years, but you also have the founder, uh, entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the person. So fing, so you make, it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. You, I still think that that's important, right? It still is a human need for people to believe in narratives and stories. But having said that you're right, the proof is in the pudding, right? At some point you click download and you try the product and it does what it says it it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy that we live in, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their products exactly >>The volume back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song was the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the, you know, it's gotta speak to >>The, speak to the user, but let me ask a question now that the people watching who are maybe entrepreneurial entrepreneur, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage, engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I >>Show >>The path. I think the single most important thing for any founder and VC relationship is that they have the same vision, uh, have the same vision. You can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens in six months. Sometimes it takes six years is sometimes like 16 years. >>Uh, what's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Desel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There, there's three big trends that we invest in. And they're the, they're the only things we do day in, day out. One is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen and on what timeline happening >>Forever. >>But it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a, a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is under invested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion. And it still is a fraction of what we're, what >>We're and security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters of your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cub gone. Uh, >>Absolutely. >>Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for having me on >>The show. Guess bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After the short break, stay with us. Everyone. Welcome to the queue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with the events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube got a great guest here. Justin Coby owner and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us a story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving into the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas up in Toronto, uh, key Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago and it's been a great ride. It >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small to midsize business. They're trying to understand how to leverage technology. It better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech ISNT really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the cloud or we move some things to cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strateg, always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want get set up. But then the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>In the SMB space? The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. >>Good. How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I, there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning the projects that early and not worrying about it, you got it. I mean, most people don't abandon cause like, oh, I own it. >>Exactly. And >>They get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say. So, oh, it's a great analogy. So I mean, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you, I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did am jazzy announce or Adam, you know, the 5,000 announcement or whatever. They do huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are, >>What's the values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your, or it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back Andre or the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner, that's all offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a fortune. If >>Training alone would be insane, a factor and the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement and still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I love it. It's amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and businesses in general, small en large, it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cybersecurity issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one and the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about. So that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side though. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And, and the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll >>Do all that >>Exactly. In it department. >>Exactly. >>Like, can we just call up, uh, you know, <laugh> our old vendor. That's >>Right. <laugh> right. Our old vendor. I like it, but that's so true. I mean, when I think about how, if I was a business owner, starting a business to today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we talk about every, with every one of our small to midsize business. >>So just, I want to get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at R I T long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that we're gonna also buy the business with >>Me. And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they care very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us and we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The game don't, won't say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing were a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud and a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on eight at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers, empathetic to where they are in their journey. And >>That's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and doubling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. Thank >>You very much for having >>Me. Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching with back with more great coverage for two days after this short break >>Live on the floor in San Francisco for 80 west summit, I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube, bringing all the action. Also virtual, we have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticketing off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad >>To be here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the, uh, New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the, the game is pretty much laid out. Mm. And the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud out for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and then became the CEO. Now Adam Slosky is in charge, but the edge has always been that thing they've been trying to, I don't wanna say, trying to avoid, of course, Amazon would listen to customers. They work backwards from the customers. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. It >>Does. >>That's not central lies in the public cloud. Now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the <affirmative> what's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over fit 15 AWS edge services, and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube, uh, cuz it's basically Amazon in a box, pushed in the data center, uh, running native, all the stuff, but now cloud native operations are kind of become standard. You're starting to see some standard Deepak sings group is doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see low the zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I wanna manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere in your VMware environment and it's increasing the speed of adoption >>For sure. So you guys are making a lot of good business decisions around managed cloud service. Innovative does that. You have the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their available ability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They wanna focus on their applications. They want focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. We help build out these things in local data centers for 32 plus year old company, we have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. >>So basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we're gonna talk about hurricanes and gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data, you have applications that are tapping into that, that requirement. It makes total sense. We're seeing across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech in, in the islands. There are a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto underly parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a tech technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. And I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead. It's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decent centralized. >>Yeah. And that's, and that's the conversation performance. >>Yeah. >>And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through a, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a and I also want all the benefits of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the good this of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-processing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take the, those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data lake or whatever, >>To the data lake. Yeah. Data Lakehouse, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but I'll lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going of the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you, what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacture, industrial, whatever the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture in the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about out. Customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern we're seeing of the past year is that throwing away data's bad, even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retraining their machine learning algorithms. Yep. So as data becomes code, as we call it in our last showcase, we did a whole whole event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw it away. It's not just business better. Yeah. There's all kinds of new scale. >>There are. And, and we have, uh, many customers that are running pay Toby level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move Aytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background, OnPrem architect, Aus cloud, and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You got a customer to jump out >>Kind of. So I was, you jumped out. I was teaching having, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a sky. I instructor, uh, I was teaching skydiving and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his customers are working. And he can't find an enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started and the first day there, uh, we had a, a discussion, uh, EC two had just come out <laugh> and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services tore >>It's. So it's such a great story, you know, was gonna, you know, you know, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You got the right equipment. You gotta do the right things. Exactly. >>Right. >>Yeah. Thanks for coming. You really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live in San Francisco for eight of us summit. I'm John for host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look up this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host of the cube. We'll be at the eighties summit in New York city this summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor in a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you. Cool. How are you? Good. >>How hello you. >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you, never after to see you. Uh, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. We have raised close to a hundred million there. The investors are people like Norwes Menlo ventures, coastal ventures, Ram Shera, and all those people, all well known guys. And Beckel chime Paul me Mayard web. So whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take you to the next stage? Well, >>I love having you on the cube, Dave and I, Dave LAN as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know, who does >>You, >>You >>Get the call fund to talk to you though. You >>Get the commentary, your, your finger in the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a $2 billion valuation back from the dead after they pivoted from enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control plan? Emerging AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 billion observability companies. Data is the key. This is what's your end on this. What's your take. >>Yeah, look, I think I'll give you the few that I see right from my side. Obviously data is very clear. So the things that rumor system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA AI enable is a new buzzword and using the AI for customer service. It, you talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI services. What used to be desk with ServiceNow BMC GLA you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you, you see AI going >>Off is RPA. A company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, is it a product company? I mean, or I mean, RPA is, should be embedded in everything. It's a >>Feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be embedded in every area. Yeah. Like we call cloud NATO and AI. They it'll become automation data. Yeah. And that's your, thinking's >>Interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So remember the databases became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you, you were talking about, it should be part of service. Now it should be part of ISRA. Like every company, every Salesforce. So that's why you see it MuleSoft and sales buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer embedded inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind, as you got the XPO hall got, um, we're back to vis, but you got, you know, AMD, Clum, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right? Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs, what does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be people don't just build on Amazon. They're going to build it on top of snow. Flake companies are snowflake becomes a data platform, right? People will build on snowflake, right? So I see my old boss playing ment, try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer, right? So I think that's the next level of companies trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last re invent, coined the term super cloud, right? It's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of hitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer room. The middle layer pass will be snowflake. So I cannot build it on snowflake. I can use them for data layer if I really need to size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll >>See. So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It >>Is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got Redshift. Um, but snowflake big customer. The they're probably paying AWS big, >>I >>Think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with the snowflake to have native snowflake data warehouse as a data layer. So I think depending on the use case you have to use each of the above, I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose your value. That's right. With some sort of internal hack, but I've think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it closed skill you the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless. Even the customer service service. Now the ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the market. Feel free to text me or DMing. Next question is really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean seeing some stuff, but why don't we get your thoughts on that? What it >>Is you, if I remember going back to our 2007 or eight, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a C I will line our business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. Yeah. >>And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I, I reference the URL causes like there's like a bunch of companies we've been promoting because the solution that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share? >>I, a lot of thoughts that Fu I see the AI op solutions in the futures should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to pro so solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers give the data, share the data because we thought the data algorithms are useless. I can give the best algorithm, but I gotta train them, modify them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know that >>Look at, look how much data bricks has grown. >>It is doubled. The key cloud >>Air kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking year that growing customers and my customers, or some of them, you like it's zoom auto desk, McAfee, uh, grand <inaudible>. So all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours. One area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of a us summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on the calendar, of course, go to a us startups.com. That's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be two with the cube on the set. We're getting back in the Groove's psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economist with duck bill groove, he's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit posting, but they don't know how to do it. They're >>Doing it right. There's something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what, what is shitposting >>It's more or less talking about the world of enterprise technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream, but it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a Jack ass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, Cuban coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's evolving Atos, especially new CEO. Andy move on to be the chief of all. Amazon just saw him the cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble. Imagine the logistics, it takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense, the nominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to a, is trying to portray themselves, you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it's same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car, our driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, it sounds like more exciting. Like they >>Better have a replacement ready in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula, the one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other people in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. Oh, >>It's great too. And I can see the appeal of these tech companies getting it into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great SA we've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late leads there been tick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's hi, I'm emailing an awful lot of people at last week in AWS every week and okay. They not have heard me. It. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, I >>Think >>I guarantee if we had that right now, people would call in and Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave Avante about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish, but that's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their product >>They're going in different directions. When they named Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonus on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, a session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store with is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage through parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, RedShift's not an acronym. You got >>Gas is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, >>They still got bean stock or is that still >>Around? Oh, they never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it, John. >>Okay. >>Simple BV still haunts our >>Dreams. I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, gimme something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay, so as Amazon gets better in some areas where do they need more work? And you, your opinion, because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So, you know, Redshift, snowflake database is out there. So you've got this optician. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Loves that term. Yeah. >>You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the, the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah. Cool. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journey mean in the, in the cloud journey, going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna end, certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing, or just big changes you've seen with the pan endemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who >>Can pony. >>Hello and welcome back to the live cube coverage here in San Francisco, California, the cube live coverage. Two days, day two of a summit, 2022 Aish summit, New York city coming up in summer. We'll be there as well. Events are back. I'm the host, John fur, the Cub got great guest here. Johnny Dallas with Ze. Um, here is on the queue. We're gonna talk about his background. Uh, little trivia here. He was the youngest engineer ever worked at Amazon at the age. 17 had to get escorted into reinvent in Vegas cause he was underage <laugh> with security, all good stories. Now the CEO of company called Z know DevOps kind of focus, managed service, a lot of cool stuff, Johnny, welcome to the cube. >>Thanks John. Great. >>So tell a story. You were the youngest engineer at AWS. >>I was, yes. So I used to work at a company called Bebo. I got started very young. I started working when I was about 14, um, kind of as a software engineer. And when I, uh, it was about 16. I graduated out of high school early, um, working at this company Bebo, still running all of the DevOps at that company. Um, I went to reinvent in about 2018 to give a talk about some of the DevOps software I wrote at that company. Um, but you know, as many of those things were probably familiar with reinvent happens in a casino and I was 16. So was not able to actually go into the, a casino on my own. Um, so I'd have <inaudible> security as well as casino security escort me in to give my talk. >>Did Andy jazzy, was he aware of >>This? Um, you know, that's a great question. I don't know. <laugh> >>I'll ask him great story. So obviously you started a young age. I mean, it's so cool to see you jump right in. I mean, I mean you never grew up with the old school that I used to grew up in and loading package software, loading it onto the server, deploying it, plugging the cables in, I mean you just rocking and rolling with DevOps as you look back now what's the big generational shift because now you got the Z generation coming in, millennials on the workforce. It's changing like no one's putting and software on servers. Yeah, >>No. I mean the tools keep getting better, right? We, we keep creating more abstractions that make it easier and easier. When I, when I started doing DevOps, I could go straight into E two APIs. I had APIs from the get go and you know, my background was, I was a software engineer. I never went through like the CIS admin stack. I, I never had to, like you said, rack servers, myself. I was immediately able to scale. I was managing, I think 2,500 concurrent servers across every Ables region through software. It was a fundamental shift. >>Did you know what an SRE was at that time? >>Uh, >>You were kind of an SRE on >>Yeah, I was basically our first SRE, um, was familiar with the, with the phrasing, but really thought of myself as a software engineer who knows cloud APIs, not a SRE. All >>Right. So let's talk about what's what's going on now as you look at the landscape today, what's the coolest thing that's going on in your mind in cloud? >>Yeah, I think the, I think the coolest thing is, you know, we're seeing the next layer of those abstraction tools exist and that's what we're doing with Z is we've basically gone and we've, we're building an app platform that deploys onto your cloud. So if you're familiar with something like Carku, um, where you just click a GitHub repo, uh, we actually make it that easy. You click a GI hub repo and it will deploy on ALS using a AWS tools. So, >>Right. So this is Z. This is the company. Yes. How old's the company about >>A year and a half old now. >>All right. So explain what it does. >>Yeah. So we make it really easy for any software engineer to deploy on a AWS. It's not SREs. These are the actual application engineers doing the business logic. They don't really want to think about Yamo. They don't really want to configure everything super deeply. They want to say, run this API on S in the best way possible. We've encoded all the best practices into software and we set it up for you. Yeah. >>So I think the problem you're solving is that there's a lot of want be DevOps engineers. And then they realize, oh shit, I don't wanna do this. Yeah. And some people want to do it. They loved under the hood. Right. People love to have infrastructure, but the average developer needs to actually be as agile on scale. So that seems to be the problem you solve. Right? >>Yeah. We, we, we give way more productivity to each individual engineer, you know? >>All right. So let me ask you a question. So let me just say, I'm a developer. Cool. I build this new app. It's a streaming app or whatever. I'm making it up cube here, but let's just say I deploy it. I need your service. But what happens about when my customers say, Hey, what's your SLA? The CDN went down from this it's flaky. Does Amazon have, so how do you handle all that SLA reporting that Amazon provides? Cuz they do a good job with sock reports all through the console. But as you start getting into DevOps <affirmative> and sell your app, mm-hmm <affirmative> you have customer issues. How do you, how do you view that? Yeah, >>Well, I, I think you make a great point of AWS has all this stuff already. AWS has SLAs. AWS has contract. Aw has a lot of the tools that are expected. Um, so we don't have to reinvent the wheel here. What we do is we help people get to those SLAs more easily. So Hey, this is AWS SLA as a default. Um, Hey, we'll fix you your services. This is what you can expect here. Um, but we can really leverage S's reliability of you. Don't have to trust us. You have to trust ALS and trust that the setup is good there. >>Do you handle all the recovery or mitigation between, uh, identification say downtime for instance? Oh, the server's not 99% downtime. Uh, went down for an hour, say something's going on? And is there a service dashboard? How does it get what's the remedy? Do you have a, how does all that work? >>Yeah, so we have some built in remediation. You know, we, we basically say we're gonna do as much as we can to keep your endpoint up 24 7 mm-hmm <affirmative>. If it's something in our control, we'll do it. If it's a disc failure, that's on us. If you push bad code, we won't put out that new version until it's working. Um, so we do a lot to make sure that your endpoint stay is up, um, and then alert you if there's a problem that we can't fix. So cool. Hey S has some downtime, this thing's going on. You need to do this action. Um, we'll let you know. >>All right. So what do you do for fun? >>Yeah, so, uh, for, for fun, um, a lot of side projects. <laugh> uh, >>What's your side hustle right now. You got going on >>The, uh, it's >>A lot of tools playing tools, serverless. >>Yeah, painless. A lot of serverless stuff. Um, I think there's a lot of really cool WAM stuff as well. Going on right now. Um, I love tools is, is the truest answer is I love building something that I can give to somebody else. And they're suddenly twice as productive because of it. Um, >>It's a good feeling, isn't it? >>Oh yeah. There's >>Nothing like tools were platforms. Mm-hmm <affirmative>, you know, the expression, too many tools in the tool. She becomes, you know, tools for all. And then ultimately tools become platforms. What's your view on that? Because if a good tool works and starts to get traction, you need to either add more tools or start building a platform platform versus tool. What's your, what's your view on a reaction to that kind of concept debate? >>Yeah, it's a good question. Uh, we we've basically started as like a, a platform. First of we've really focused on these, uh, developers who don't wanna get deep into the DevOps. And so we've done all of the pieces of the stacks. We do C I C D management. Uh, we do container orchestration, we do monitoring. Um, and now we're, spliting those up into individual tools so they can be used. Awesome in conjunction more. >>All right. So what are some of the use cases that you see for your service? It's DevOps basically nano service DevOps. So people who want a DevOps team, do clients have a DevOps person and then one person, two people what's the requirements to run >>Z. Yeah. So we we've got teams, um, from no DevOps is kind of when they start and then we've had teams grow up to about, uh, five, 10 men DevOps teams. Um, so, you know, as is more infrastructure people come in because we're in your cloud, you're able to go in and configure it on top you're we can't block you. Uh, you wanna use some new AWS service. You're welcome to use that alongside the stack that we deploy >>For you. How many customers do you have now? >>So we've got about 40 companies that are using us for all of their infrastructure, um, kind of across the board, um, as well as >>What's the pricing model. >>Uh, so our pricing model is we, we charge basically similar to an engineering salary. So we charge a monthly rate. We have plans at 300 bucks a month, a thousand bucks a month, and then enterprise plan for >>The requirement scale. Yeah. So back into the people cost, you must have her discounts, not a fully loaded thing, is it? >>Yeah, there's a discounts kind of asking >>Then you pass the Amazon bill. >>Yeah. So our customers actually pay for the Amazon bill themselves. So >>Have their own >>Account. There's no margin on top. You're linking your, a analyst account in, um, got it. Which is huge because we can, we are now able to help our customers get better deals with Amazon. Um, got it. We're incentivized on their team to drive your costs down. >>And what's your unit main unit of economics software scale. >>Yeah. Um, yeah, so we, we think of things as projects. How many services do you have to deploy as that scales up? Um, awesome. >>All right. You're 20 years old now you not even can't even drink legally. <laugh> what are you gonna do when you're 30? We're gonna be there. >>Well, we're, uh, we're making it better, better, >>Better the old guy on the queue here. <laugh> >>I think, uh, I think we're seeing a big shift of, um, you know, we've got these major clouds. ALS is obviously the biggest cloud and it's constantly coming out with new services, but we're starting to see other clouds have built many of the common services. So Kubernetes is a great example. It exists across all the clouds and we're starting to see new platforms come up on top that allow you to leverage tools for multiple times. At the same time. Many of our customers actually have AWS as their primary cloud and they'll have secondary clouds or they'll pull features from other clouds into AWS, um, through our software. I think that's, I'm very excited by that. And I, uh, expect to be working on that when I'm 30. <laugh> awesome. >>Well, you gonna have a good future. I gotta ask you this question cuz uh, you know, I always, I was a computer science undergrad in the, in the, and um, computer science back then was hardcore, mostly systems OS stuff, uh, database compiler. Um, now there's so much compi, right? Mm-hmm <affirmative> how do you look at the high school college curriculum experience slash folks who are nerding out on computer science? It's not one or two things. You've got a lot of, lot of things. I mean, look at Python, data engineering and emerging as a huge skill. What's it, what's it like for college kids now and high school kids? What, what do you think they should be doing if you had to give advice to your 16 year old self back a few years ago now in college? Um, I mean Python's not a great language, but it's super effective for coding and the datas were really relevant, but it's, you've got other language opportunities you've got tools to build. So you got a whole culture of young builders out there. What should, what should people gravitate to in your opinion and stay away from or >>Stay away from? That's a good question. I, I think that first of all, you're very right of the, the amount of developers is increasing so quickly. Um, and so we see more specialization. That's why we also see, you know, these SREs that are different than typical application engineering. You know, you get more specialization in job roles. Um, I think if, what I'd say to my 16 year old self is do projects, um, the, I learned most of my, what I've learned just on the job or online trying things, playing with different technologies, actually getting stuff out into the world, um, way more useful than what you'll learn in kind of a college classroom. I think classroom's great to, uh, get a basis, but you need to go out and experiment actually try things. >>You know? I think that's great advice. In fact, I would just say from my experience of doing all the hard stuff and cloud is so great for just saying, okay, I'm done, I'm banning the project. Move on. Yeah. Cause you know, it's not gonna work in the old days. You have to build this data center. I bought all this, you know, people hang on to the old, you know, project and try to force it out there. Now you >>Can launch a project now, >>Instant gratification, it ain't working <laugh> or this is shut it down and then move on to something new. >>Yeah, exactly. Instantly you should be able to do that much more quickly. Right. So >>You're saying get those projects and don't be afraid to shut it down. Mm-hmm <affirmative> that? Do you agree with that? >>Yeah. I think it's ex experiment. Uh, you're probably not gonna hit it rich on the first one. It's probably not gonna be that idea is the genius idea. So don't be afraid to get rid of things and just try over and over again. It's it's number of reps >>That'll win. I was commenting online. Elon Musk was gonna buy Twitter, that whole Twitter thing. And someone said, Hey, you know, what's the, I go look at the product group at Twitter's been so messed up because they actually did get it right on the first time. And we can just a great product. They could never change it because people would freak out and the utility of Twitter. I mean, they gotta add some things, the added button and we all know what they need to add, but the product, it was just like this internal dysfunction, the product team, what are we gonna work on? Don't change the product so that you kind of have there's opportunities out there where you might get the lucky strike right outta the gate. Yeah. Right. You don't know. >>It's almost a curse too. It's you're not gonna hit curse Twitter. You're not gonna hit a rich the second time too. So yeah. >><laugh> Johnny Dallas. Thanks for coming on the cube. Really appreciate it. Give a plug for your company. Um, take a minute to explain what you're working on. What you're look looking for. You hiring funding. Customers. Just give a plug, uh, last minute and kind the last word. >>Yeah. So, um, John Dallas from Ze, if you, uh, need any help with your DevOps, if you're a early startup, you don't have DevOps team, um, or you're trying to deploy across clouds, check us out z.com. Um, we are actively hiring. So if you are a software engineer excited about tools and cloud, or you're interested in helping getting this message out there, hit me up. Um, find us on z.co. >>Yeah. LinkedIn Twitter handle GitHub handle. >>Yeah. I'm the only Johnny on a LinkedIn and GitHub and underscore Johnny Dallas underscore on Twitter. All right. Um, >>Johnny Dallas, the youngest engineer working at Amazon, um, now 20 we're on great new project here in the cube. Builders are all young. They're growing into the business. They got cloud at their, at their back it's tailwind. I wish I was 20. Again, this is a I'm John for your host. Thanks for watching. Thanks. >>Welcome >>Back to the cubes. Live coverage of a AWS summit in San Francisco, California events are back, uh, ADAS summit in New York cities. This summer, the cube will be there as well. Check us out there lot. I'm glad we have events back. It's great to have everyone here. I'm John furry host of the cube. Dr. Matt wood is with me cube alumni now VP of business analytics division of AWS. Matt. Great to see you. Thank >>You, John. Great to be here. >>Appreciate it. I always call you Dr. Matt wood, because Andy jazzy always says Dr. Matt, we >>Would introduce you on the he's the one and only the one and >>Only Dr. Matt wood >>In joke. I love it. >>Andy style. And I think you had walkup music too on, you know, >>Too. Yes. We all have our own personalized walk. >>So talk about your new role. I not new role, but you're running up, um, analytics, business or AWS. What does that consist of right now? >>Sure. So I work, I've got what I consider to be the one of the best jobs in the world. Uh, I get to work with our customers and, uh, the teams at AWS, uh, to build the analytics services that millions of our customers use to, um, uh, slice dice, pivot, uh, better understand their day data, um, look at how they can use that data for, um, reporting, looking backwards and also look at how they can use that data looking forward. So predictive analytics and machine learning. So whether it is, you know, slicing and dicing in the lower level of, uh Hado and the big data engines, or whether you're doing ETR with glue or whether you're visualizing the data in quick side or building models in SageMaker. I got my, uh, fingers in a lot of pies. >>You know, one of the benefits of, uh, having cube coverage with AWS since 2013 is watching the progression. You were on the cube that first year we were at reinvent 2013 and look at how machine learning just exploded onto the scene. You were involved in that from day one is still day one, as you guys say mm-hmm <affirmative>, what's the big thing now. I mean, look at, look at just what happened. Machine learning comes in and then a slew of services come in and got SageMaker became a hot seller, right outta the gate. Mm-hmm <affirmative> the database stuff was kicking butt. So all this is now booming. Mm-hmm <affirmative> that was the real generational changeover for <inaudible> what's the perspective. What's your perspective on, yeah, >>I think how that's evolved. No, I think it's a really good point. I, I totally agree. I think for machine machine learning, um, there was sort of a Renaissance in machine learning and the application of machine learning machine learning as a technology has been around for 50 years, let's say, but, uh, to do machine learning, right? You need like a lot of data, the data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute. You need to be able to train the models <laugh> and so where you go. >>And so the cloud really enabled this Renaissance with machine learning, and we're seeing honestly, a similar Renaissance with, uh, with data, uh, and analytics. You know, if you look back, you know, five, 10 years, um, analytics was something you did in batch, like your data warehouse ran a analysis to do, uh, reconciliation at the end of the month. And then was it? Yeah. And so that's when you needed it, but today, if your Redshift cluster isn't available, uh, Uber drivers don't turn up door dash deliveries, don't get made. It's analytics is now central to virtually every business and it is central to every virtually every business is digital transformation. Yeah. And be able to take that data from a variety of sources here, or to query it with high performance mm-hmm <affirmative> to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form, you know, wisdom and information from raw data. That's kind of, uh, what most organizations are trying to do when they kind of go through this analytics journey. It's >>Interesting, you know, Dave LAN and I always talk on the cube, but out, you know, the future and, and you look back, the things we were talking about six years ago are actually happening now. Yeah. And it's not a, a, a, you know, hyped up statement to say digital transformation. It actually's happening now. And there's also times where we bang our fist on the table, say, I really think this is so important. And Dave says, John, you're gonna die on that hill <laugh>. >>And >>So I I'm excited that this year, for the first time I didn't die on that hill. I've been saying data you're right. Data as code is the next infrastructure as code mm-hmm <affirmative>. And Dave's like, what do you mean by that? We're talking about like how data gets and it's happening. So we just had an event on our 80 bus startups.com site mm-hmm <affirmative>, um, a showcase with startups and the theme was data as code and interesting new trends emerging really clearly the role of a data engineer, right? Like an SRE, what an SRE did for cloud. You have a new data engineering role because of the developer on, uh, onboarding is massively increasing exponentially, new developers, data science, scientists are growing mm-hmm <affirmative> and the, but the pipelining and managing and engineering as a system. Yeah. Almost like an operating system >>And as a discipline. >>So what's your reaction to that about this data engineer data as code, because if you have horizontally scalable data, you've gotta be open that's hard. <laugh> mm-hmm <affirmative> and you gotta silo the data that needs to be siloed for compliance and reasons. So that's got a very policy around that. So what's your reaction to data as code and data engineering and >>Phenomenon? Yeah, I think it's, it's a really good point. I think, you know, like with any, with any technology, uh, project inside an organization, you know, success with analytics or machine learning is it's kind of 50% technology and then 50% cultural. And, uh, you have often domain experts. Those are, could be physicians or drug experts, or they could be financial experts or whoever they might be got deep domain expertise. And then you've got technical implementation teams and it's kind of a natural often repulsive force. I don't mean that rudely, but they, they just, they don't talk the same language. And so the more complex the domain and the more complex the technology, the stronger that repulsive force, and it can become very difficult for, um, domain experts to work closely with the technical experts, to be able to actually get business decisions made. And so what data engineering does and data engineering is in some cases team, or it can be a role that you play. >>Uh, it's really allowing those two disciplines to speak the same language it provides. You can think of it as plumbing, but I think of it as like a bridge, it's a bridge between like the technical implementation and the domain experts. And that requires like a very disparate range of skills. You've gotta understand about statistics. You've gotta understand about the implementation. You've gotta understand about the, it, you've gotta understand and understand about the domain. And if you could pull all of that together, that data engineering discipline can be incredibly transformative for an organization, cuz it builds the bridge between those two >>Groups. You know, I was advising some, uh, young computer science students at the sophomore junior level, uh, just a couple weeks ago. And I told 'em, I would ask someone at Amazon, this questions I'll ask you since you're, you've been in the middle of of it for years, they were asking me and I was trying to mentor them on. What, how do you become a data engineer from a practical standpoint, uh, courseware projects to work on how to think, um, not just coding Python cause everyone's coding in Python mm-hmm <affirmative> but what else can they do? So I was trying to help them and I didn't really know the answer myself. I was just trying to like kind of help figure it out with them. So what is the answer in your opinion or the thoughts around advice to young students who want to be data engineers? Cuz data scientists is pretty clear in what that is. Yeah. You use tools, you make visualizations, you manage data, you get answers and insights and apply that to the business. That's an application mm-hmm <affirmative>, that's not the, you know, sta standing up a stack or managing the infrastructure. What, so what does that coding look like? What would your advice be to >>Yeah, I think >>Folks getting into a data engineering role. >>Yeah. I think if you, if you believe this, what I said earlier about like 50% technology, 50% culture, like the, the number one technology to learn as a data engineer is the tools in the cloud, which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the, the storage is kind of fungible or UND differentiated. That that's really not the case. Success requires you to really purpose built well crafted high performance, low cost engines for all of your data. So understanding those tools and understanding how to use 'em, that's probably the most important technical piece. Um, and yeah, Python and programming and statistics goes along with that, I think. And then the most important cultural part, I think is it's just curiosity. >>Like you want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem and to be able to engage, cuz you're probably, you're gonna have some choice as you go through your career about which domain you end up in, like maybe you're really passionate about healthcare. Maybe you're really just passionate about your transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity, but within those roles, like the domains are so broad, you kind of gotta allow your curiosity to develop and lead, to ask the right questions and engage in the right way with your teams. So because you can have all the technical skills in the world, but if you're not able to help the team's truths seek through that curiosity, you simply won't be successful. >>We just had a guest on 20 year old, um, engineer, founder, Johnny Dallas, who was 16 when he worked at Amazon youngest engineer at >>Johnny Dallas is a great name by the that's fantastic. It's his real name? >>It sounds like a football player. Rockstar. I should call Johnny. I have Johnny Johnny cube. Uh it's me. Um, so, but he's young and, and he, he was saying, you know, his advice was just do projects. >>Yeah. That's get hands on. >>Yeah. And I was saying, Hey, I came from the old days though, you get to stand stuff up and you hugged onto the assets. Cause you didn't wanna kill the cause you spent all this money and, and he's like, yeah, with cloud, you can shut it down. If you do a project that's not working and you get bad data, no one's adopting it or you don't want like it anymore. You shut it down. Just something >>Else. Totally >>Instantly abandoned it. Move onto something new. >>Yeah. With progression. Totally. And it, the, the blast radius of, um, decisions is just way reduced, gone. Like we talk a lot about like trying to, you know, in the old world trying to find the resources and get the funding. And it's like, right. I wanna try out this kind of random idea that could be a big deal for the organization. I need 50 million in a new data center. Like you're not gonna get anywhere. You, >>You do a proposal working backwards, document >>Kinds, all that, that sort of stuff got hoops. So, so all of that is gone, but we sometimes forget that a big part of that is just the, the prototyping and the experimentation and the limited blast radius in terms of cost. And honestly, the most important thing is time just being able to jump in there, get fingers on keyboards, just try this stuff out. And that's why at AWS, we have part of the reason we have so many services because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so, as your ideas developed, you may want to jump from, you know, data that you have, that's already in a database to doing realtime data. Yeah. And then you can just, you have the tools there. And when you want to get into real time data, you don't just have kineses, but you have real time analytics and you can run SQL again, that data is like the, the capabilities and the breadth, like really matter when it comes to prototyping and, and >>That's culture too. That's the culture piece, because what was once a dysfunctional behavior, I'm gonna go off the reservation and try something behind my boss's back or cause now as a side hustle or fun project. Yeah. So for fun, you can just code something. Yeah, >>Totally. I remember my first Haddo project, I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for like another month. And I installed her DUP on them and like, got them going. It's like, that just seems crazy to me now that I, I had to go and convince anybody not to turn these service off, but what >>It was like for that, when you came up with elastic map produce, because you said this is too hard, we gotta make it >>Easier. Basically. Yes. <laugh> I was installing Haddo version, you know, beta nor 0.9 or whatever it was. It's like, this is really hard. This is really hard. >>We simpler. All right. Good stuff. I love the, the walk down memory lane and also your advice. Great stuff. I think culture's huge. I think. And that's why I like Adam's keynote to reinvent Adam. Lesky talk about path minds and trail blazers because that's a blast radius impact. Mm-hmm <affirmative> when you can actually have innovation organically just come from anywhere. Yeah, that's totally cool. Totally. Let's get into the products. Serverless has been hot mm-hmm <affirmative> uh, we hear a lot about EKS is hot. Uh, containers are booming. Kubernetes is getting adopted. There's still a lot of work to do there. Lambda cloud native developers are booming, serverless Lambda. How does that impact the analytics piece? Can you share the hot, um, products around how that translates? Sure, absolutely. Yeah, the SageMaker >>Yeah, I think it's a, if you look at kind of the evolution and what customers are asking for, they're not, you know, they don't just want low cost. They don't just want this broad set of services. They don't just want, you know, those services to have deep capabilities. They want those services to have as lower operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, lot of services about getting up and running and experimenting and prototyping and turning things off and turn turning them on and turning them off. And like, that's all great. But actually the, you really only most projects start something once and then stop something once. And maybe there's an hour in between, or maybe there's a year, but the real expense in terms of time and, and complexity is sometimes in that running cost. Yeah. And so, um, we've heard very loudly and clearly from customers that they want, that, that running cost is just undifferentiated to them and they wanna spend more time on their work and in analytics that is, you know, slicing the data, pivoting the data, combining the data, labeling the data, training their models, uh, you know, running inference against their models, uh, and less time doing the operational pieces. >>So is that why the servers focus is there? >>Yeah, absolutely. It, it dramatically reduces the skill required to run these, uh, workloads of any scale. And it dramatically reduces the UND differentiated, heavy lifting, cuz you get to focus more of the time that you would've spent on the operation on the actual work that you wanna get done. And so if you look at something just like Redshift serverless that we launched a reinvent, you know, there's a kind of a, we have a lot of customers that want to run like a, uh, the cluster and they want to get into the, the weeds where there is benefit. We have a lot of customers that say, you know, I there's no benefit for me though. I just wanna do the analytics. So you run the operational piece, you're the experts we've run. You know, we run 60 million instant startups every single day. Like we do this a lot. Exactly. We understand the operation. I >>Want the answers come on. So >>Just give the answers or just let, give me the notebook or just give the inference prediction. So today for example, we announced, um, you know, serverless inference. So now once you've trained your machine learning model, just, uh, run a few, uh, lines of code or you just click a few buttons and then yeah, you got an inference endpoint that you do not have to manage. And whether you're doing one query against that endpoint, you know, per hour or you're doing, you know, 10 million, but we'll just scale it on the back end. You >>Know, I know we got not a lot of time left, but I want, wanna get your reaction to this. One of the things about the data lakes, not being data swamps has been from what I've been reporting and hearing from customers is that they want to retrain their machine learning algorithm. They want, they need that data. They need the, the, the realtime data and they need the time series data, even though the time has passed, they gotta store in the data lake mm-hmm <affirmative>. So now the data lakes main function is being reusing the data to actually retrain. Yeah, >>That's >>Right. It worked properly. So a lot of, lot of postmortems turn into actually business improvements to make the machine learning smarter, faster. You see that same way. Do you see it the same way? Yeah, >>I think it's, I think it's really interesting. No, I think it's really interesting because you know, we talk it's, it's convenient to kind of think of analytics as a very clear progression from like point a point B, but really it's, you are navigating terrain for which you do not have a map and you need a lot of help to navigate that terrain. Yeah. And so, you know, being, having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed, and we added PII detection today, you know, something you can do automatically, uh, to be able to use their, uh, any unstructured data run queries against that unstructured data. So today we added, you know, um, text extract queries. So you can just say, well, uh, you can scan a badge for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. So there's a often a, it's more like a branch than it is just a, a normal, uh, a to B path, a linear path. Uh, and that includes loops backwards. And sometimes you gotta get the results and use those to make improvements further upstream. And sometimes you've gotta use those. And when you're downstream, you'll be like, ah, I remember that. And you come back and bring it all together. So awesome. It's um, it's, uh, uh, it's a wonderful >>Work for sure. Dr. Matt wood here in the queue. Got just take the last word and give the update. Why you're here. What's the big news happening that you're announcing here at summit in San Francisco, California, and update on the, the business analytics >>Group? Yeah, I think, you know, one of the, we did a lot of announcements in the keynote, uh, encouraged everyone to take a look at that. Uh, this morning was Swami. Uh, one of the ones I'm most excited about, uh, is the opportunity to be able to take, uh, dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, uh, all over the place. However, what we've heard from customers is like, yes, I want those analytics. I want their visualization. I want it to be up to date, but you know, I don't actually want to have to go my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced, uh, one click public embedding for quick side dashboards. So today you can literally, as easily as embedding a YouTube video, you can take a dashboard that you've built inside, quick site cut and paste the HTML, paste it into your application and that's it. That's all you have to do. It takes seconds and >>It gets updated in real time. >>Updated in real time, it's interactive. You can do everything that you would normally do. You can brand it like this is there's no power by quick site button or anything like that. You can change the colors, make it fit in perfectly with your, with your applications. So that's sitting incredibly powerful way of being able to take a, uh, an analytics capability that today sits inside its own little fiefdom and put it just everywhere. It's, uh, very transformative. >>Awesome. And the, the business is going well. You got the serverless and your tailwind for you there. Good stuff, Dr. Matt with thank you. Coming on the cube >>Anytime. Thank >>You. Okay. This is the cubes cover of eight summit, 2022 in San Francisco, California. I'm John host cube. Stay with us with more coverage of day two after this short break.

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack into both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges in particular insuring consistent and predictable application performance is tricky especially because containers, they're so flexible and they enable portability. Things are constantly changing. DevOps pros have to way through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes resources and kills operational efficiency. So teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns is Matt Provo, founder and CEO of StormForge. Matt, welcome to theCUBE. Good to see you. >> Good to see you. Thanks for having me. >> Yeah, so we saw you guys at a KubeCon sort of first introduce you to our community but add a little color to my intro there if you will. >> Yeah, well, Semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago, we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over, sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn. And developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news. You had launch coming to further address these problems. Tell us about that. >> Yeah, so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we've kind of been single threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly amazing results. My vision has been for us to be able to close the loop, however, between data coming out of pre-production and the associated optimizations and data coming out of production environment and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the a second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed... And I used to ask, you know, technology companies all the time. Okay, so you're telling me beforehand what the optimal configuration should be and resource allocation. What happens if something changes? >> Yeah. >> And then it's always, always a pause. >> Yeah. >> And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah, so we view what happens in pre-production as sort of the experimentation phase. And our machine learning is allowing the user to experiment in scenario plan. What we're doing with Optimize Live and adding the the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint is with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this edition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that no else is doing from the standpoint of closing that loop. >> So you said front machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah, I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning or AI gets tagged to a lot of stuff. It's very buzzwordy. It looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab. And that was our focus. We then decided, we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yes, so when you... Many organizations today have an existing monitoring APM observability suite really in place. They've also got a metric source. So this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than, really than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the the tool set or, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the requests I'm going to allow application and what are the limits? So what are those thresholds that I'm going to be okay with so that I can, again, try to hit my business objectives and keep in line with my SLAs? And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over are the recommendations and manually deploy them into their environment themselves. And we, again, really believe that the user knows their application. They know the goals that they have and we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team? >> Yep. >> And then your system is smart enough to adapt and address those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who's hosting a Drupal, one of the largest Drupal hosts. So it's all do it yourself across thousands of customers so it's, you know, very unpredictable. I want to make something clear though as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit into the ecosystem. >> Yeah, so it's a great point. We're also, you know, a series B startup and growing. We've the choice to be very intentionally focused on the problems that we've solve. And we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We are really an intelligence platform. And that intelligence and insights that we're able to draw is because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to to Datadog or Dynatrace or Splunk or AppDynamics or some of the other. And we're totally fine with that. They've got great market share and penetration. They do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive. They're visualized and somewhat reactive. And we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think, Matt, about cloud native and I go back to the sort of origins of CNCF who's a, you know, handful of companies. And now you look at the participants it'll, you know, make your eyes bleed. How do you address dealing with all those companies and what is the partnership strategy? >> Yeah, it's so interesting because it's just that even that CNCF landscape has exploded. It was not too long ago where it was as small or smaller than the FinOps landscape today which by the way, the FinOps piece is also on a a neck breaking, you know, growth curve. We, I do see, although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain, you know, with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM uses of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and that specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically a few other cloud providers that are operating, manage Prometheus environments. >> Okay, so where do you want to take this thing? You're not taking the observability guys head on, smart move. So many of those even entering the market now. But what is the vision? >> Yeah, so we've had this debate a lot as well 'cause it's super difficult to create a category. You know, on one hand, you know, I have a lot of respect for founders and companies that do that. On the other hand from a market timing standpoint, you know we fit into AIOps, that's really where we fit. You know, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint, that's our bet. But we're an AIOps platform. You know, we'll continue getting better at the problems we solve with machine learning and we'll continue adding data inputs. So we'll go, you know, we'll go beyond the application layer which is really where we play now. We'll add, you know, kind of whole cluster optimization capabilities across the full stack. And the way we will get there is by continuing to add different data inputs that make sense across the different layers of the stack. And it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space, you can just play right into that. >> Yeah. >> The more data you get because your purpose built to solving these types of problems. >> Yeah, so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. >> Excellent, Matt, thank you so much. >> Thanks for having me. >> Appreciate for coming on. Okay, keep it right there in a moment. We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier. They went through a major replatforming with Kubernetes on AWS. You're watching theCUBE, you are leader in enterprise tech coverage. (bright upbeat music)

(upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from enterprise technology research shows Kubernetes specifically, leads the pack into both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges, in particular ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and they enable portability, things are constantly changing. DevOps Pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes resources and kills operational efficiency. So teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns is Matt Provo, founder and CEO of StormForge. Matt, welcome to The CUBE. Good to see you. >> Good to see you. Thanks for having me. >> Yeah. So we saw you guys at CUBE con, sort of first introduce you to our community, but add a little color to my intro there if you want. >> Well, you semi stole my thunder, but I'm okay with that. Absolutely agree with everything you said in the intro. The problem that we have set out to solve, which is tailor made for the use of real machine learning, not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago, we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today, as they're moving more workloads over, sort of drink the cool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn and developers in many ways love it. Once they start to operationalize use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively and ensuring and implementing the right kind of automation that empowers developers into the process, ultimately does not automate them out of it. >> So you've got news, you a hard launch coming to further address these problems. Tell us about that. >> Yeah. So historically, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we've kind of been single threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly, amazing results. My vision has been for us to be able to close the loop, however, between data coming out of pre-production and the associated optimizations and data coming out of production environment and our ability to optimize that. A lot of our users along the way have said, these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce, kind of the second core module for our platform called optimized live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed, and I used to ask technology companies all the time. Okay. So you're telling me beforehand what the optimal configuration should be and resource allocation, what happens if something changes? And then it's always, always a pause. And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So this is specifically the problem you're addressing, maybe talk about that a little bit more. >> Yeah. So we view what happens in pre-production as sort of the experimentation phase. And our machine learning is is allowing the user to experiment and scenario plan. What we're doing with optimized live and adding the production piece is what we kind of also call, kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint is aligning with your SLOs and your SLAs, as well as your business objectives. And so that's the entire point of this edition, is to allow our users to experience, hopefully the the Nirvana associated with that, because it's an exciting opportunity for them and really something that nobody else is doing from the standpoint of closing that loop. >> So you said up front, machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah. I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning or AI gets tagged to a lot of stuff. It's very buzz wordy, it looks good. I'm fortunate to have found a number of folks from the outset of the company with PhDs and applied mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so for the first three or four years of the company's history, we really operated as a lab. And that was our focus. We then decided, we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all these pain points around, how fast the adoption of containers and Kubernetes have taken place, but the pain that developers are running into, we actually found for ourselves that this was the perfect use case. >> So how specifically does optimize live work? Can you add a little detail on that? >> Yeah. So when you... Many organizations today have an existing monitoring APM, observability suite really in place, they've also got a metric source. So this could be something like Datadog, or Prometheus. And once that data starts flowing there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the vertical pod auto scaler. And less than, really less than 1% of Kubernetes users take advantage of of the VPA, mostly because it's really challenging to configure and it's not super compatible with the tool set or the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this world for developers is they're having to make decisions on a number of different metrics or resource elements, typically things like memory and CPU, and they have to decide, what are the requests I'm going to allow for this application and what are the limits? So what are those thresholds that I'm going to be okay with? So that I can, again, try to hit my business objectives and keep in line with my SLAs. And to your earlier point in the intro, it's often guesswork. They either have to rely on out of the box recommendations that ship with the databases and other services that they are using, or it's a super manual process to go through and try to configure and tune this. And so with optimized live, we're making that one click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy, or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves. And we, again, really believe that the user knows their application. They know the goals that they have, we don't, but we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team. And then your system is smart enough to a adapt and address those? >> Application over application. And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who's hosting a Drupal, one of the largest Drupal hosts. So it's all do it yourself across that of customers. So it's very unpredictable. I want to make something clear though. As to where you fit in the ecosystem, you're not an observability platform, you leverage observability platforms. So talk about that and where you fit in into the ecosystem. >> Yeah. So this is a great point. We're also a series B startup and growing where we've the choice to be very intentionally focused on the problems that we've solve and we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We are really an intelligence platform and that intelligence and insights that we're able to draw is because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to Datadog or Dynatrace or Splunk or UpDynamics or some of the other. And we're totally fine with that. They've got great market share and penetration. They do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive, they're visualized and somewhat reactive and we make those, we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think Matt about cloud native and I go back to the sort of origins of CNCF, it was a handful of companies, and now you look at the participants make your eyes bleed. How do you address dealing with all those companies and what's the partnership strategy? >> Yeah, it's so interesting because, just that even that CNCF landscape has exploded. It was not too long ago where it was as small or smaller than the Finops landscape today, which by the way, the Finops piece is also on a neck breaking growth curve. I do see, although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain with our customers and users. And so we've made strategic and intentional decisions on deep partnerships, in some cases like OEM, uses of our technology and certainly, intelligent and seamless integrations into a few. So we'll be announcing a really exciting partnership with AWS and that specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus, and specifically a few other cloud providers that are operating manage Prometheus environments. >> Okay. So where do you want to take this thing? You're not taking the observability guys head on, smart move. So many of those even entering the market now. But what is the vision? >> Yeah. So we've had this debate a lot as well 'cause it's super difficult to create a category. On one hand, I have a lot of respect for founders and companies that do that, on the other hand, from a market timing standpoint, we fit into AI Ops, that's really where we fit. We've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint that's our bet, but we're an AI Ops platform, we'll continue getting better at the problems we solve with machine learning and we'll continue adding data inputs. So we'll go beyond the application layer, which is really where we play now. We'll add kind of whole cluster optimization capabilities across the full stack. And the way we will get there is by continuing to add different data inputs that make sense across the different layers of the stack. And it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space, you can just play right into that? More data you get because your purpose built to solving these types of problems. >> Yeah. So you can imagine a world right now out of observability, we're taking things like telemetry data. Pretty quickly you can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow. It just feeds our own, we are reliant on data. >> Excellent. Matt, thank you so much. Appreciate you coming on. >> Thanks for having me. >> Okay. Keep it right there. In a moment, we're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier. They went through a major replatforming with Kubernetes on AWS. You're watching The CUBE, your leader in enterprise tech coverage. (upbeat music)

[Music] the adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise i.t survey data from enterprise technology research shows kubernetes specifically leads the pack in both spending velocity and market share now like virtualization in its early days containers bring many new performance and tuning challenges in particular ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and they enable portability things are constantly changing devops pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error this endless cycle taxes resources and kills operational efficiency so teams often just capitulate and simply dial up and throw unnecessary resources at the problem stormforge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis and with me to talk about a new offering that directly addresses these concerns is matt provo founder and ceo of stormforge matt welcome to the cube good to see you good to see you thanks for having me yeah so we saw you guys at a kubecon sort of first introduce you to our community but add a little color to my intro there yeah well you semi stole my thunder but uh i'm okay with that uh absolutely agree with everything you said in the intro um you know the the problem that we have set out to solve which is tailor-made for the use of real machine learning not machine learning kind of as a as a marketing tag uh is is connected to how workloads on kubernetes are are really managed from a resource efficiency standpoint and so a number of years ago we built uh the the core machine learning engine and have now turned that into a platform around how kubernetes resources are managed at scale and so organizations today as they're moving more workloads over uh sort of drink the kool-aid of the flexibility that comes with kubernetes and how many knobs you can turn and developers in many many ways love it once they start to operationalize the use of kubernetes and move uh workloads from pre-production into production they run into a pretty significant complexity wall and and this is where stormforge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it so you've got news yeah hard launch coming and to further address these problems tell us about that yeah so historically um uh you know like any machine learning engine we think about data inputs and what kind of data is going to feed our our system to be able to draw the appropriate insights out out for the user and so historically we are we've kind of been single threaded on load and performance tests in a pre-production environment and there's been a lot of adoption of that a lot of excitement around it and and frankly amazing results my vision has been uh for us to be able to close the loop however between uh data coming out of pre-production and opt in the associated optimizations and data coming out of production a production environment uh and and our ability to optimize that a lot of our users along the way have have said these results in pre-production are are fantastic how do i know they reflect reality of what my application is going to experience in a production environment and so we're super excited to to announce kind of the second core module for our platform called optimizelive the data input for that is uh observability and telemetry data coming out of apm platforms and and other data sources so this is like nirvana so i wonder if we could talk a little bit more about the the challenges that this address is i mean i've been around a while and it really have observed and i used to ask you know technology companies all the time okay so you're telling me beforehand what the optimal configuration should be and resource allocation what happens if something changes yeah and then it's always always a pause yeah and kubernetes is more of a rapidly changing environment than anything we've ever seen yeah so this is specifically the problem you're addressing maybe talk about that yeah so we view what happens in pre-production as sort of the experimentation phase and our machine learning is is allowing the user to experiment and design and scenario plan what we're doing uh with optimize live and adding the the production piece is uh what we kind of also call kind of our observation phase and so you need to be able to to to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance from a cost standpoint is aligning with your slos and your slas as well as your business objectives and so that's the entire point of of this edition is to is to allow our users uh to experience uh hopefully the nirvana associated with that because it's an exciting er it's an exciting opportunity for them and really something that uh nobody else is doing from the standpoint of of closing that loop so you said upfront machine learning not as a marketing tag so i want you to sort of double click on that what's different than how other companies approach this problem yeah i mean part of it is a bias for me and a frustration as a founder of of the reason i started the company in the first place i think machine learning or ai gets tagged to a lot of stuff it's very buzz wordy it's it looks good i'm fortunate to have found a number of folks from the outset of the company with you know phds in applied mathematics and a focus on actually building real ai at the core uh that is connected to solving the right kind of actual business problems and so you know for the first three or four years of the company's history we really operated as a lab and that was our our focus we were we then decided we're trying to connect a fantastic team with differentiated technology to the right market timing and when we saw all these pain points around how fast the adoption of containers and kubernetes have taken place but the pain that the developers are running into we found it we actually found for ourselves uh that this was the perfect use case so how specifically does optimize live work can you add a little detail on that yeah so when you um many organizations today have an existing monitoring apm observability suite really in in place they've also got they've also got a metric source so this could be something like datadog or prometheus and once that data starts flowing there's an out of the box or or kind of a piece of kubernetes that ships with it called the vpa or the vertical pod auto scaler and uh less than really less than one percent of kubernetes users take advantage of the of the vpa mostly because it's really challenging to configure and it's not super compatible with the the tool set or the eco you know the ecosystem of tools uh in a kubernetes environment and so our biggest competitor is the vpa and what's happening in this environment or in in this world for developers is they're having to make decisions on on a number of different metrics or or resource elements typically things like memory and cpu and they have to decide what are the what are the limitations what are the requests i'm going to allow for this uh application and what are the limits so what are those thresholds that i'm going to be okay with so that i can again try to hit my business objectives and keep in line with my slas and to your earlier point in the intro it's often guesswork um you know they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this and so with optimize live we're making that one click and so we're continuously and consistently uh observing and watching the data that's flowing through these tools and we're serving back recommendations for the user they can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves and we again really believe that the the user knows their application they know their the goals that they have we don't uh but we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations so the business objectives are an input from the application team yeah and then your system is smart enough to adapt and address those application over application right and and so the the thresholds in any given organization across their different ecosystem of apps or environment could be different the business objectives could be different and so we don't want to predefine that for people we want to give them the opportunity to build those thresholds in and then allow the machine learning to uh to learn and to send recommendations within those bounds and we're going to hear later from a customer who's uh hosting a drupal one of the largest drupal hosts so it's all do-it-yourself across thousands of customers so it's you know very unpredictable i want to make something clear though as to where you fit in the ecosystem you're not an observability platform you leverage observability platforms right so talk about that and where you fit in into the ecosystem yeah so that's a great point um we uh we're also you know a series b startup and and growing where we've made the choice to be very intentionally focused on the problems that we've solved and we've uh chosen to partner or integrate otherwise and so we do get put into the apm category from from time to time we're really an intelligence platform and that intelligence and insights that we're able to draw is because we because of the core machine learning we've built over the years and we also don't want organizations or users to have to switch from tools and investments that they've already made and so we were never going to we were never going to catch up to to to datadog or dynatrace or or splunk or app dynamics or some of the other and and we're totally fine with that they've got great market share and penetration they they do solve real problems instead we felt like users would want a seamless integration uh into the the tools they're already using and so we we we view ourselves as uh kind of the intel inside uh for that kind of a scenario and uh it takes observability and apm data and insights that were somewhat reactive uh they're visualized and somewhat reactive and and we make those uh we add that we add that proactive nature onto it the insights and and ultimately the the appropriate level of automation so when i think matt about cloud native and i go back to the sort of origins of cncf it was a handful of companies and now you look at the participants it'll you know make your eyes bleed how do you address dealing with all those companies and what are the what's the partnership strategy yeah it's so interesting because um it's just that even that cncf landscape has exploded um it was not too long ago where it was as small or smaller than the finnops landscape today which by the way the phenops pieces is also on a neck-breaking you know growth curve we i do see although there are a lot of companies and a lot of tools we're starting to see a significant amount of consistency or hardening of the tool chain uh you know for with our customers and end users and so we've made strategic and intentional decisions on deep partnerships in some cases like oem uh uses of our technology and and certainly you know intelligent and seamless integrations uh into a few so you know we're we'll be announcing uh a really exciting partnership with aws uh and and uh specifically what they're doing with eks their their kubernetes distribution and services we've got a deep partnership and integration with datadog and then with prometheus and specifically cloud provider a few other cloud providers that are operating managed prometheus environments okay so where do you want to take this thing it's not you're not taking the observability guys head on smart move so many of those even entering the market now but what is the vision yeah so we've had this debate a lot as well because it's super difficult to create a category uh you know on one hand um you know you know i have a lot of respect for founders and and companies that do that on the other hand um from a market timing standpoint you know we fit into ai ops that's really where we fit um you know we are we've made a bet on the future of kubernetes uh and and what that's going to look like and so um from a containers and kubernetes standpoint that's our bet uh but we're an aiops platform you know we'll continue getting better at what at the problems we solve with machine learning and we'll continue adding data inputs so we'll go you know we'll go beyond the application layer which is really where we play now we'll add kind of whole cluster optimization capabilities across across the full stack and the way we'll get there is by continuing to add different data inputs that make sense across the different layers of the stack and it's exciting we can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time so that's your next concentric circle as the observability vendors expand their observation space you can just play right into that yeah more data you get because you're a purpose built to solving these types of problems yeah so you can imagine a world right now out of observability we're taking things like telemetry data pretty quickly you can imagine a world where we take traces and logs and other data inputs as as that ecosystem continues to grow it just feeds our own uh you know we are reliant on data um so excellent matt thank you so much appreciate you for having me okay keep it right there in a moment we're gonna hear from a customer with a highly diverse and constantly changing environment that i mentioned earlier they went through a major re-platforming with kubernetes on aws you're watching thecube your leader in enterprise tech coverage [Music] you

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack in both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges. In particular, ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and the enabled portability things are constantly changing. DevOps pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes, resources, and kills operational efficiencies so teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded in mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns, is Matt Provo, founder and CEO of StormForge. Matt, welcome to thecube. Good to see you. >> Good to see you, thanks for having me. >> Yeah. So we saw you guys at CubeCon, sort of first introduce you to our community but add a little color to my intro if you will. >> Yeah, well you semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn and developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news, your hard launch coming in to further address these problems. Tell us about that. >> Yeah so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we are, we've kind of been single-threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly, amazing results. My vision has been for us to be able to close the loop however between data coming out of pre-production and the associated optimizations and data coming out of production, a production environment, and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed and I used to ask technology companies all the time, okay, so you're telling me beforehand what the optimal configuration should be in resource allocation, what happens if something changes? And then it's always a pause. And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So this is specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah so we view what happens in pre-production as sort of the experimentation phase and our machine learning is allowing the user to experiment and scenario plan. What we're doing with Optimize Live and adding the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint, is aligning with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this addition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that nobody else is doing from the standpoint of closing that loop. >> So you said upfront machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning our AI gets tagged to a lot of stuff. It's very buzzwordy, it looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab and that was our focus. We then decided we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all of these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we found it, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yeah so when you, many organizations today have an existing monitoring APM observability suite really in place. They've also got, they've also got a metric source, so this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than really less than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the tool set or the, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the, what are the requests I'm going to allow for this application and what are the limits? So what are those thresholds that I'm going to be okay with? So that I can again try to hit my business objectives and keep in line with my SLAs. And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one-click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves. And we again, really believe that the user knows their application, they know the goals that they have, we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team and then your system is smart enough to adapt and adjust those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who is hosting a Drupal, one of the largest Drupal host, is it? So it's all do it yourself across thousands of customers so it's very unpredictable. I want to make something clear though, as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit in into the ecosystem. >> Yeah so it's a great point. We, we're also you know, a series B startup and growing. We've made the choice to be very intentionally focused on the problems that we've solve and we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We're really an intelligence platform. And that intelligence and insights that we're able to draw is because we, because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to Datadog or Dynatrace or Splunk or AppDynamics or some of the other, and we're totally fine with that. They've got great market share and penetration and they do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive, they're visualized and somewhat reactive and we make those, we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think Matt about cloud native and I go back to the sort of origins of CNCF, it was a, you know, handful of companies, and now you look at the participants, you know, make your eyes bleed. How do you address dealing with all those companies and what's the partnership strategy? >> Yeah it's so interesting because it's just that even at CNCF landscape has exploded. It was not too long ago where it was as smaller than the finOps Landscape today which by the way the FinOps pieces is also on a neck breaking, you know, growth curve. We, I do see although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM users of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically cloud provider, a few other cloud providers that are operating manage Prometheus environments. >> Okay so where do you want to take this thing? If it's not, you're not taking the observability guys head on, smart move, so many of those even entering the market now, but what is the vision? >> Yeah so we've had this debate a lot as well because it's super difficult to create a category. You know, on one hand, I have a lot of respect for founders and companies that do that, on the other hand from a market timing standpoint, you know, we fit into AIOps. That's really where we fit. You know we are, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint that's our bet. But we're an AIOps platform, we'll continue getting better at what, at the problems we solve with machine learning and we'll continue adding data inputs so we'll go beyond the application layer which is really where we play now. We'll add kind of whole cluster optimization capabilities across the full stack. And the way we'll get there is by continuing to add different data inputs that make sense across the different layers of the stack and it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space you can just play right into that. The more data you get could be because you're purpose built to solving these types of problems. >> Yeah so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. So. >> Excellent. Matt, thank you so much. Thanks for hoping on. >> Yeah, appreciate it. >> Okay. Keep it right there. In a moment, We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier, they went through a major re-platforming with Kubernetes on AWS. You're watching theCube, your a leader in enterprise tech coverage. (bright music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante full stack observability is the new buzz phrase as businesses go digital customer experience becomes ever more important why because fickle consumers can switch brands in the blink of an eye or the click of a mouse every vendor wants a piece of the action in this market including companies that have provided traditional monitoring log analytics application performance management etc and they're joined by a slew of new entrants claiming end invisibility across the so-called modern tech stack recent survey research from etr however confirms our thesis that no one company has it all new entrants they've got a vision and and they're not encumbered with legacy technical debt however their offerings are immature on the other hand established players with deep feature sets in one segment are pivoting through m a and some organic development to fill gaps meanwhile the cloud players are well positioned and participating through a combination of their own native tooling combined with strong ecosystems in their respective marketplaces to address this opportunity hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we dive into a recent etr drill down study on full stack observability and to do so we once again welcome in our colleague eric bradley chief engagement strategist and director of research at etr eric good to see you my friend thanks for coming on uh always good to be here dave thank you so much for having us we appreciate it all right before we get into the survey eric i i want to talk a little bit about full stack observability define what it is and so let me start and then you can chime in so when people talk about full stack observability they're referring to the need to understand the behavior of all the technology components that support an application i.e the stack right throughout the entire system meaning the full piece of the equation right the entire system so the compute we're talking about the storage the network and of course that's all software defined today the containers that are running the software the database other middleware components the pipeline of data and then of course the client-side code everything the html the css everything down to the mobile device and the idea is to give people who can fix problems full visibility into the system with a dashboard of metrics that can be visualized at a high level and then drilled into to see logs or traces or events all the metrics that could help remediate an issue so a simple way to think about this eric is i like to think of it as the ability to see everything in the tech stack that could impact the customer experience right how do you see it if only we're that simple right it's it's a huge thing that we're trying to encompass there with full stack observability and uh even though the vendors might tell you on the first sales call that they can do it it's really not that simple based on everything you just said um in this particular survey we tried our best to look at it and we'll go into it later but you know we had to survey on the application side infrastructure side database side blog management security network it's a very difficult thing to encompass um the holy grail would be able to do it with one vendor and do it with one dashboard i don't think we're there anytime soon all right so let's get into this drill down survey results and talk about what you've learned first what is explain what a drill down study is how often does etr conduct these types of things you know who responds what can you tell us yeah sure so the drill downs are actually basically think of it as a custom type of survey work and that could be customized from two different ways either our clients will come to us with a particular topic and we will hold their hands and make sure that they get the the responses that they need uh and more often than not it's actually us as a research department uh wanting to dig into trends that our larger data encompasses and then we'll say hey we really need to look into that and we've done it with everything from rpa to identity access to you know hearing observability and also vendor specific and and macro trends as you know david this particular one the genesis was really a large amount of interest not only from our community the end users but clients i i can't tell you how much interest there is in observability right now we're constantly getting questions and demands for more research and deeper research in this space yeah so our audience will be familiar with the concept of net score that's the periodic survey every quarter like clockwork etr does that then in addition as eric was saying hot topics like in this case full stack observability so we're talking about respondents in the etr community in this case who have a deep understanding of observability and related topics and and they had varying degrees of knowledge about each vendor's offering so you asked the respondents to concentrate on the ones that they knew well correct yes that is correct so this was a smaller survey that we did the end was a little under 188 i believe um and essentially what we did was we took people that responded in the bigger study on these observability vendors and then sent this drill down out so they were specifically people that have purview over their spend with observability now some of it might be more database infrastructure application or security but everyone here is already qualified as an expert to answer these questions that's correct dave yeah so the first data point is the one we're showing you right here the respondents were asked who uses observability tools and eric i've highlighted app ops in in the site reliability engineers because given the emphasis on customer centricity that we hear all the time from the vendor community you would think these roles would be more highly represented but it's the folks in the boiler room that are using these tools highly technical and specialized roles what are your thoughts on this data you know i was a little surprised as well i i kind of thought the sres would be a little bit higher on this but it really just comes down to you know it's the infrastructure um devops and secops that seem to be using it the most i thought maybe the application operations teams would be a little bit more involved as well so i agree with you i was a little bit surprised on this but you know they're the experts so we have to take the data at their word for it but i think what's really happening here is you're recognizing that the work is being done across the entire enterprise as you mentioned before about full stack this isn't just one aspect it's touching every aspect of the enterprise and that's including the internal i.t teams well and i think too eric that this what i took away from this drill down and we'll get more into it is that the vendor marketing is not aligned with what's actually happening in the field and so there's these early days we'll talk about that some more okay next question i thought this was very interesting etr asked on the scale of one to three three being most preferred which pricing model host-based user-based or amount of data ingested based pricing that the responders preferred and eric so what are your what are your thoughts on this because just doing a quick scan scan pricing is all over the map yeah it really is all over the map from a vendor perspective right and also from an end user perspective and all the interviews and panels that i host pricing's a real concern but it is always but in this particular field it's a real concern and i actually just did a panel yesterday of four of these 88 survey takers to get a little bit deeper so i'm going to kind of remark on what they taught me a little bit yesterday one of them said ingestion pricing might be preferable but because it's so unpredictable that's why we're seeing the results skew away from it another one went so far that said uh ingestion based pricing is a nightmare that keeps him up at night because he's just so afraid he's gonna wake up the next day and see what the bill is so um really what they're looking for here and the reason the pricing is skewing that way in this survey is because they need predictability it's about their budget and it's about their planning even though they would prefer an ingestion-based model the fact that they have to plan for their budgets and they have to concern themselves with spending it's moving more to host based yeah so i mean it is complicated and because so for example i just took a quick snapshot of some of the pricing models like dynatrace appd datadog aws and others they tout their host-based pricing new relic they have a splash page up around its user-based pricing and the tiers datadog talks about its ingestion-based pricing for security monitoring aws prices by ingestion for cloud watch logs splunk prices on index data and calculates a per gigabyte per day metric so metrics dashboards alarms alerts events it's they could all be priced differently yeah that's true a few that got called out on us and i'm sure we're going to get into them later so i don't want to you know kill all of our fodder right now but when we were talking about this slide one person particularly decided to call out new relic and specif specifically for their flexibility around pricing he said that they have the ability to rapidly scale up but also contract as needed and he actually even though he's a user of splunk he's a user of dyna trees user of elastic um he also just really wanted to call out the flexibility of new relic in this area so to your point there's a lot of different ways to price this it's a complex problem but i think the key takeaway for vendors is flexibility is the key you really need to give people the ability to be flexible in what they want all right let's drill into the functionality and explore the usage and adoption of the different features by the respondents so this next chart shows module adoption for application performance monitoring apm database and digital experience down to the user and eric i underlined apm which is the blue bar because it seems it stands out especially for aws and you can see dynast dyna trace but also azure new relic and splunk and then digital experience which is the gray bar because despite all the chatter in the market and the marketing around digital transformation and customer experience other than a slightly higher response percentage for aws not a lot of adoption on that front so the vendor marketing again doesn't match the user behavior does it eric no it doesn't there's a couple of things to point out here but let's stick with that digital experience i i was surprised that it was so low on this slide and overall in our survey i did expect it to be more and not just from the vendor marketing perspective but you and i both know at the end of the day the whole point of this is to actually get into that 360 view of what your customer's doing so i i was a little bit surprised to see it that low when we spoke to the panel yesterday a couple of people said no listen it's not that we aren't doing that it's just that it's not the vendors that you put on this survey and they called out two particular names one is called catchpoint and the other one is thousand dies and i think you're aware a thousand dice i'm going to transition that off to you there yeah so a thousand eyes is now part of cisco and we're gonna talk about that a little bit later but but essentially like as i was saying up front they've got gaps in their in their product line so they've got to do m a and then package that up so you know we'll we'll get into that a little bit down the road but i want to bring up the next graphic because that looks at incident management infrastructure monitoring and log management and and what i did here is i called out infrastructure monitoring which is the gray bar and log management that light blue because aws and azure they stand out in these categories and splunk of course eric for for log management what what do you take away from this data yeah the previous slide and this slide you really have to call out aws cloudwatch and microsoft is your monitor um they are very pervasive in this survey and we could probably do an entire show on just that on the cloud versus independent but a couple of things i do want to point out even though these numbers are so high for these cloud tools the the panelists and the people i spoke to in more detail all said listen i'm going to look at my cloud tools first i'm on their infrastructure they're handing it to me i'm going to look at it and i'll use it for what it's good for however we're in a multi-cloud world and they're not good at things that aren't in their ecosystem so these are not even though these numbers are high i do not believe that you know aws or azure is going to go and take over all the independents in a multi-cloud world they want an independent vendor whether it's a data dog new relic we could talk about all of those later but um you know really i was surprised that the aws particularly was so high and so pervasive in here across the way a splunk what can you say i mean they are the most pervasive vendor you know they they're everywhere uh we had people in the panel call them a swiss army knife and you know that's a good and a bad that they have a lot of breadth of coverage which is great but because there's a breadth of coverage not all of it is great log management without a doubt is what they are great at they're specialized at it but the panelists were saying listen if you go away from their core and you try to use some of the other things they claim that they can do it requires a lot of heavy lifting and then we can get into a little bit later about their cloud cloud sas integration we had some issues with that in the survey as well and great points about the multi-cloud you're probably not going to trust that to your your cloud your public cloud vendor and so a lot of white space available for the traditional on-prem guys okay next the etr survey drilled into network monitoring and security monitoring and then other security functions and eric there are a couple of things that stood out to me in this chart i highlighted security monitoring which is the blue bar because you can again see the adoption from aws and azure and of course splunk and also we called out solar winds because of the large adoption in network monitoring so let me ask you what are you seeing in the data since the solarwinds breach and is there anything else in this chart that you want to call out i could go on for a while about solarwinds but you know the data since i guess it broke around 12 months ago even though the breach was even prior to that uh the headlines were big i think you remember you and i last year did a quick drill down survey just on solarwinds uh and the impact that we thought we would have it uh there's a very real impact happening uh with that said they're not easy to move away from um we asked about is there any one vendor that could take this entire space and the answer was solar winds was best positioned to do that but it's too late now and then i drilled down a little bit and i asked the panel well what can they do to reinvent themselves what can they do to change the reputational damage from this breach and the panelists all said nothing the reputational damage is done the best way for them to reinvent themselves would be to do an m a consolidate with somebody else change their name they truly believe that right now the only reason that people are still using solarwinds is it's not that easy to lift and shift away from but there will be no new net workloads going to these people at least according to the the ones who took our survey um that's on solar winds and we could get you know in more if you want but i think that's kind of you know giving the the the crux of the matter on splunk again what can you say on the security side on the sim side people don't want to use multiple vendors on the other side we were talking about with full stack some might be better at apm some might be better at infrastructure monitoring when you're talking about security you truly do want one vendor to rule them all and splunk does seem to be the one that's most well entrenched on the security side and as long as the policy is consistent across security you really can't say much about them so what they do well their core their the data shows that you know people still trust them great thank you for that okay now the last set of data we want to show we kind of consolidated some things you want the the detail and the drill down you had several drill down questions and what we try to do is consolidate them into a single chart which we had to stare at for a while so for each of the 11 companies etr asked respondents if the features across the top that you see here were strengths weaknesses or neutral and what we've done is we tried to consolidate the chart showing the strengths in the green which we just subjectively said okay that means more than 40 percent of the respondents identified the feature as a strength the weaknesses in yellow meant that more than 20 percent of the respondents cited the feature as a weakness and the neutrals in the gray where neither of those conditions were met but the gray was you know the neutral was high and what we did is we added four stars for standout features where 60 or more of the respondents cited the feature as a strength and we threw in two stars if they were close to 60 you know high 50s even mid 50s but but not single digit weakness for that feature that was got two stars so it was able to sort of visualize a lot of data so eric just a quick scan of this chart chart shows that the two big cloud players aws in particular but also azure they have a relatively strong showing and i say relatively because as you know eric there wasn't a single category of feature for any vendor where more than 70 percent of the respondents cited the strength for that single feature not one and there was a lot of gray and you can see pricing is a sore point for many customers including those evaluating solarwinds new relic elastic datadog dynatrace appd and splunk only aws and grafana were hit not hit hard on pricing and i guess the other thing that stands out to me here is that new relic eric showed some relative strength so the last thing i'll mention before you dive in look at what cisco is doing we talked about this before a little bit the drill down focused on appd but as i mentioned earlier companies that have mature stacks are filling the gaps so if you look at what cisco's doing this space they've put an interface layer over appd inner site and thousand eyes even though they're separate products they're historically priced separately i think they're still trying to figure out the pricing but they are definitely going to market with a strategy that bolts together these three separate products and that's not necessarily a bad strategy because combined they can claim even more depth and breadth eric what do you make of this data yeah just like this chart there is a lot there right so uh on a macro level let's just the obvious situation here is this is a crowded crowded marketplace and consolidation is needed i had one panelist say to me yesterday i can't wait for this to consolidate like this is just crazy that there needs to be consolidation uh now to your point about cisco cisco's taking the same playbook they did with security right they're going out and they're buying great tools and then now we have to make sure that they figure out a way to integrate these better uh the security side took them a little while to do that but they're getting there hopefully they can do this a little bit quicker here what we did here is that um appd is actually very strong on the application monitoring side for the core apm uh maybe not so much on these others and then that's why they go out and do what you're doing what you're saying about now so hopefully they will get there um kind of talking across the board pricing was a problem for all of them right so it just seems to me that you know the end users the buyers just feel like hey i shouldn't be paying this much for this we've got a lot of choices maybe there's some collusion on the pricing side but we have to figure it out because they do not want to pay this much for it it was the number one concern across almost every single vendor another aspect that i really want to call out on this and is something that our research team found really interesting and it's really about the digital transformation as digital transformation continues the workloads are moving towards the cloud and we're clearly seeing in this data that that's benefiting the newer players the data dogs and the new relics versus some of the others like a dynatrace and a splunk and when you go and actually look at the cloud sas integration answer option specifically it becomes very very obvious um you know splunk had a 38 on that number whereas datadog had 61 new relic at 58. so it's just very clear as a digital transformation increases workloads on observability it is lifting all boats but it's lifting some faster than others great points um all right as we said at the top you've got a set of incumbents they're jockeying for position you've got companies like datadog it's got as eric just mentioned strong cloud model elastic's got got the open source mojo and they're going after splunk's install base as is datadog and then you see startups like chaos search they're out now talking about how to do log analytics they do more than that but that's their sort of starter use case and they're going after the elastic and the elk stack which got dinged a bit in the survey on simplicity uh you know ease of standing it up and and so forth not a weakness if you're comfortable with full open source model but maybe not well understood as some of the other solution oriented plays and then you got other new entrants which are not covered in the drill down they're not as pervasive in the marketplace but guys like honeycomb and observe eric you mentioned some others that came out in the panel vmware even is getting into the act they're positioning tanzu around observability with really a strong kubernetes emphasis and there's dozens of other players in the space which we haven't talked about so eric this is jump ball and i'll give you the final word give us your last thoughts yeah there's a again a lot there it's such an interesting space like even ibm right they go out and buy turbonomics right everyone seems to be playing and not only that the ones that are already playing are expanding data dog comes out and says hey we do security now so i don't really know where this is going to end but there's too much happening there needs to be some sort of you know order out of the chaos uh to your point about some of the emerging names we just launched our emerging technology survey this week david those are the ones where we're going to see data on those names so stay tuned for that we don't track them in the core tsis which are more mature public vendors but we will be getting some data on those uh but to your point i really do believe that this space is rapidly expanding and i just kind of want to leave everyone with this there's a lot of growth still left in the panel yesterday i basically said to people how much of your infrastructure are you monitoring today versus how much you want to and the answer was around 65 to 70 percent being monitored now and without a doubt they all want to get to 100 so there is still a lot of room to grow in this space but i just don't know if there's enough room for all of these people that are basically going after the same percentage points so what we're seeing from a vendor strategy now is bundling they're trying to bundle because that's the way they're gonna actually gain that market share right and uh just one last point to you for elastic a lot of people still view elastic as a search functionality so even though they have use cases and observability i still think there's a lot of people that the elastic got into the elk stack in general got into their enterprise for search so that is still kind of where they are and maybe they're not moving as fast as a data dog or a new relic in pure full stack observability eric so great to have you on you guys cover so much space so we're gonna leave it there for now we really appreciate our friends at etr for the the work that they do and thank you eric for joining us today and sharing your insights great stuff welcome dave i always enjoy talking to you you know that and uh everyone else we'll be back in a couple of months with our predictions as well so yeah that's right yeah look for those all right remember these episodes are all available as podcasts wherever you listen all you gotta do is search breaking analysis podcast check out etr's website etr dot plus they've got a whole new packaging and and pricing models so check that out we also publish a full report every week on wikibon.com and siliconangle.com and you can get in touch with me david.velante at siliconangle.com or at divalante on twitter i'm on linkedin all the time this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well and we'll see you next time you

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Every CEO is figuring out the right balance for new hybrid business models. Now, regardless of the chosen approach, which is going to vary, technology executives, they understand they have to accelerate their digital and build resilience as well as optionality into their platforms. Now, this is driving a dramatic shift in IT investments. And at the macro level, we expect total spending to increase at as much as 8% or even more in 2021, compared to last year's contraction. Investments in cybersecurity, cloud collaboration that are enabling hybrid work as well as data, including analytics, AI, and automation are at the top of the spending priorities for CXOs. Hello everyone. And welcome to this week's Wiki Bond Cube insights, powered by ETR. In this Breaking Analysis, we're pleased to welcome back Erik Bradley, who is the chief engagement strategist at our partner, ETR. Now in this segment, we're going to share some of the latest findings from ETR's surveys and provide our commentary on what it means for the markets, for sellers, and for buyers. Erik, great to see you, my friend. Welcome back to Breaking Analysis. >> Thank you for having me, always enjoy it. We've got some fresh data to talk about on this beautiful summer Friday, so I'm ready to go. >> All right. I'm excited too. Okay, last year we saw a contraction in IT spending by at least 5%. And now we're seeing a snapback to, as I said, at least 8% growth relative to last year. You got to go back to 2007 just before the financial crisis to see this type of top line growth. The shift to hybrid work, it's exposed us to new insidious security threats. And we're going to discuss that in a lot more detail. Cloud migration of course picked up dramatically last year, and based on the recent earnings results of the big cloud players, for now we got two quarters of data, that trend continues as organizations are accelerating their digital platform build-outs, and this is bringing a lot of complexity and a greater need for so-called observability solutions, which Erik is going to talk about extensively later on in this segment. Data, we think is entering a new era of de-centralization. We see organizations not only focused on analytics and insights, but actually creating data products. Leading technology organizations like JP Morgan, they're heavily leaning into this trend toward packaging and monetizing data products. And finally, as part of the digital transformation trend, we see no slow down in spending momentum for AI and automation, generally in RPA specifically. Erik, anything you want to add to that top level narrative? >> Yeah, there's a lot to take on the macro takeaways. The first thing I want to state is that that 8, 8.5% number that started off at just 3 to 4% beginning of the year. So as the year has continued, we are just seeing this trend in budgets continue to accelerate, and we don't have any reason to believe that's going to stop. So I think we're going to just keep moving on heading into 2021. And we're going to see a banner year of spend this year and probably next as well. >> All right, now we're going to bring up a chart that shows kind of that progression here of spending momentum. So Erik, I'm going to let you comment on this chart that tracks those projections over time. >> Erik: Yeah. Great. So thank you very much for pulling this up. As you can see in the beginning part of the year, when we asked people, "What do you plan to spend throughout 2021?" They were saying it would be about a 4% increase. Which we were happy with because as you said last year, it was all negative. That continues to accelerate and is only hyper accelerating now as we head into the back half of the year. In addition, after we do this data, I always host a panel of IT end users to kind of get their feedback on what we collected, to a man, every one of them expects continued increase throughout next year. There are some concerns and uncertainty about what we're seeing right now with COVID, but even with that, they're planning their budgets now for 2022 and they're planning for even further increases going forward. >> Dave: Great, thank you. So we circled that 8%. That's really kind of where we thought it was going to land. And so we're happy with that number, but let's take a look at where the action is by technology sector. This chart that we're showing you here, it tracks spending priorities back to last September. When I believe that was the point, Erik, that cyber became the top priority in the survey, ahead of cloud collaboration, analytics, and data, and the other sectors that you see there. Now, Erik, we should explain. These areas, they're the top seven, and they outrank all the other sectors. ETR tracks many, many other sectors, but please weigh in here and share your thoughts on this data. >> Erik: Yeah. Security, security, security. It hasn't changed. It had really hasn't. The hybrid work. The fact that you're behind the firewall one day and then you're outside working from home the next, switching in and out of networks. This is just a field day for bad actors. And we have no choice right now, but to continue to spend, because as you're going to talk about in a minute, hybrid's here to stay. So we have to figure out a way to secure behind the firewall on-prem. We also have to secure our employees and our assets that are not in the office. So it is a main priority. One of the things that point out on this chart, I had a couple of ITN users talk to me about customer experience and automation really need to move from the right part of that chart to the left. So they're seeing more in what you were talking about in RPA and automation, starting to creep up heading into next year. As cloud migration matures, as you know, cybersecurity spending has been ramping up. People are going to see a little bit more on the analytics and a little bit more on the automation side going forward. >> Dave: Great. Now, this next data view- well, first of all, one of the great things about the ETR dataset is that you can ask key questions and get a time series. And I will tell you again, I go back to last March, ETR hit it. They were the first on the work from home trend. And so if you were on that trend, you were able to anticipate it. And a lot of investors I think took advantage of that. Now, but we've shown this before, but there's new data points that we want to introduce. So the data tracks how CIOs and IT buyers have responded to the pandemic since last March. Still 70% of the organizations have employees working remotely, but 39% now have employees fully returning to the office and Erik, the rest of the metrics all point toward positives for IT spending, although accelerating IT deployments there at the right peaked last year, as people realized they had to invest in the future. Your thoughts? >> Erik: Yeah, this is the slide for optimism, without a doubt. Of the entire macro survey we did, this is the most optimistic slide. It's great for overall business. It's great for business travel. This is well beyond just IT. Hiring is up. I've had some people tell me that they possibly can't hire enough people right now. They had to furlough employees, they had to stop projects, and they want to re accelerate those now. But talent is very hard to find. Another point to you about your automation and RPA, another underlying trend for there. The one thing I did want to talk about here is the hybrid workplace, but I believe there's another slide on it. So just to recap on this extremely optimistic, we're seeing a lot of hiring. We're seeing increased spending, and I do believe that that's going to continue. >> Yeah I'm glad you brought that up because a session that you and I did a while ago, we pointed out, it was earlier this year, that the skill shortage is one potential risk to our positive scenario. We'll keep an eye on that, but so I want to show another set of data that we've showed previously, but ETR again, has added some new questions in here. So note here that 60% of employees still work remotely with 33% in a hybrid model currently, and the CIO's expect that to land on about 42% hybrid workforce with around 30% working remotely, which is around, it's been consistent by the way on your surveys, but that's about double the historic norm, Eric. >> Erik: Yeah, and even further to your point Dave, recently I did a panel asking people to give me some feedback on this. And three of those four experts basically said to me, if we had greed run this survey right now, that even more people would be saying remote. That they believe that that number, that's saying they're expecting that number of people to be back in office, is actually too optimistic. They're actually saying that maybe if we had- cause as a survey launched about six, seven weeks ago before this little blip on the radar, before the little COVID hiccup we're seeing now, and they're telling me that they believe if we reran this now that it would be even more remote work, even more hybrid and less returned to the office. So that's just an update I wanted to offer on this slide. >> Dave: Yeah. Thank you for that. I mean, we're still in this kind of day to day, week to week, month to month mode, but I want to do a little double click on this. We're not going to share this data, but there was so much ETR data. We got to be selective. But if you double click on the hybrid models, you'll see that 50% of organizations plan to have time roughly equally split between onsite and remote with again around 30 or 31% mostly remote, with onsite space available if they need it. And Erik, very few don't plan to have some type of hybrid model, at least. >> Yeah, I think it was less than 10% that said it was going to be exclusively onsite. And again, that was a more optimistic scenario six, seven weeks ago than we're seeing right now throughout the country. So I agree with you, hybrid is here to stay. There really is no doubt about it. from everyone I speak to when, you know, I basically make a living talking to IT end users. Hybrid is here to stay. They're planning for it. And that's really the drive behind the spending because you have to support both. You have to give people the option. You have to, from an IT perspective, you also have to support both, right? So if somebody is in office, I need the support staff to be in office. Plus I need them to be able to remote in and fix something from home. So they're spending on both fronts right now. >> Okay. Let's get into some of the vendor performance data. And I want to start with the cloud hyperscalers. It's something that we followed pretty closely. I got some Wiki bond data, that we just had earnings released. So here's data that shows the Q2 revenue shares on the left-hand side in the pie and the growth rates for the big four cloud players on the right hand side. It goes back to Q1 2019. Now the first thing I want to say is these players generated just under $39 billion in the quarter with AWS capturing 50% of that number. I said 39, it was 29 billion, sorry, with AWS capturing 50% of that in the quarter. As you're still tracking around a third in Alibaba and GCP in the, you know, eight or 9% range. But what's most interesting to me, Erik, is that AWS, which generated almost 15 billion in the quarter, was the only player to grow its revenue, both sequentially and year over year. And Erik, I think the street is missing the real story here on Amazon. Amazon announced earnings on Thursday night. The company had a 2% miss on the top line revenues and a meaningful 22% beat on earnings per share. So the retail side of the business missed its revenue targets, so that's why everybody's freaked out. But AWS, the cloud side, saw a 4% revenue beat. So the stock was off more than 70% after hours and into Friday. Now to me, a mix shift toward AWS, that's great news for investors. Now, tepid guidance is a negative, but the shift to a more profitable cloud business is a huge positive. >> Yeah, there's a lot that goes into stock price, right? I remember I was a director of research back in the day. One of my analysts said to me, "Am I crazy for putting a $1,000 target on Amazon?" And I laughed and I said, "No, you're crazy if you don't make it $2,000." (both chuckling) So, you know, at that time it was basically the mix shift towards AWS. You're a thousand percent right. I think the tough year over year comps had something to do with that reaction. That, you know, it's just getting really hard. What's that? The law of large numbers, right? It's really hard to grow at that percentage rate when you're getting this big. But from our data perspective, we're seeing no slowdown in AWS, in cloud, none whatsoever. The only slowdown we're seeing in cloud is GCP. But to, you know, to focus on AWS, extremely strong across the board and not only just in cloud, but in all their data products as well, data and analytics. >> Yeah and I think that the AWS, don't forget folks, that funds Amazon's TAM expansion into so many different places. Okay. As we said at the top, the world of digital and hybrid work, and multi-cloud, it's more complicated than it used to be. And that means if you need to resolve issues, which everybody does, like poor application performance, et cetera, what's happening at the user level, you have to have a better way to sort of see what's going on. And that's what the emergence of the observability space is all about. So Erik, let me set this up and you have a lot of comments here because you've recently had some, and you always have had a lot of round table discussions with CXOs on this topic. So this chart plots net score or spending momentum on the vertical axis, and market share or pervasiveness in the dataset on the horizontal axis. And we inserted a table that shows the data points in detail. Now that red dotted line is just sort of Dave Vellante's subjective mark in the sand for elevated spending levels. And there are three other points here. One is Splunk as well off is two-year peak, as highlighted in the red, but Signal FX, which Splunk acquired, has made a big move northward this last quarter. As has Datadog. So Erik, what can you share with us on this hot, but increasingly crowded space? >> Yeah. I could talk about the space for a long time. As you know, I've gotten some flack over the last year and a half about, you know, kind of pointing out this trend, this negative trend in Splunk. So I do want to be the first one to say that this data set is rebounding. Splunk has been horrific in our data for going back almost two years now, straight downward trend. This is the first time we're seeing any increase, any positivity there. So I do want to be fair and state that because I've been accused of being a little too negative on Splunk in the past. But I would basically say for observability right now, it's a rising tide lifts all boats, if I can use a New England phrase. The data across the board in analytics for these observability players is up, is accelerating. None more so than Datadog. And it's exactly your point, David. The complexity, the increased cloud migration is a perfect setup for Datadog, which is a cloud native. It focuses on microservices. It focuses on cloud observability. Old Splunk was just application monitoring. Don't get me wrong, they're changing, but they were on-prem application monitoring, first and foremost. Datadog came out as cloud native. They, you know, do microservices. This is just a perfect setup for them. And not only is Datadog leading the observability, it's leading the entire analytics sector, all of it. Not just the observability niche. So without a doubt, that is the strongest that we're seeing. It's leading Dynatrace new Relic. The only one that really isn't rebounding is Cisco App Dynamics. That's getting the dreaded legacy word really attached to it. But this space is really on fire, elastic as well, really doing well in this space. New Relic has shown a little bit of improvement as well. And what I heard when I asked my panelists about this, is that because of the maturity of cloud migration, that this observability has to grow. Spending on this has to happen. So they all say the chart looks right. And it's really just about the digital transformation maturity. So that's largely what they think is happening here. And they don't really see it getting, you know, changing anytime soon. >> Yeah, and I would add, and you see that it's getting crowded. You saw a service now acquired LightStep, and they want to get into the game. You mentioned, you know, last deck of the elk stack is, you know, the open source alternative, but then we see a company who's raised a fair amount of money, startup, chaos search, coming in, going after kind of the complexity of the elk stack. You've got honeycomb, which has got a really innovative approach, Jeremy Burton's company observes. So you have venture capital coming in. So we'll see if those guys could be disruptive enough or are they, you know, candidates to get acquired? We'll see how that all- you know that well. The M and A space. You think this space is ripe for M and A? >> I think it's ripe for consolidation, M and A. Something has to shake out. There's no doubt. I do believe that all of these can be standalone. So we shall see what's happened to, you mentioned the Splunk acquisition of Signal FX, just a house cleaning point. That was really nice acceleration by Signal FX, but it was only 20 citations. We'd looked into this a little bit deeper. Our data scientists did. It appears as if the majority of people are just signaling spunk and not FX separately. So moving forward for our data set, we're going to combine those two, so we don't have those anomalies going forward. But that type of acquisition does show what we should expect to see more of in this group going forward. >> Well that's I want to mention. That's one of the challenges that any data company has, and you guys do a great job of it. You're constantly having to reevaluate. There's so much M and A going on in the industry. You've got to pick the right spots in terms of when to consolidate. There's some big, you know, Dell and EMC, for example. You know, you've beautifully worked through that transition. You're seeing, you know, open shift and red hat with IBM. You just got to be flexible. And that's where it's valuable to be able to have a pipeline to guys like Erik, to sort of squint through that. So thank you for that clarification. >> Thank you too, because having a resource like you with industry knowledge really helps us navigate some of those as well for everyone out there. So that's a lot to do with you do Dave, >> Thank you. It's going to be interesting to watch Splunk. Doug Merritt's made some, you know, management changes, not the least of which is bringing in Teresa Carlson to run go to market. So if you know, I'd be interested if they are hitting, bouncing off the bottom and rising up again. They have a great customer base. Okay. Let's look at some of the same dimensions. Go ahead. You got a comment? >> A few of ETR's clients looked at our data and then put a billion dollar investment into it too. So obviously I agree. (Dave laughing) Splunk is looking like it's set for a rebound, and it's definitely something to watch, I agree. >> Not to rat hole in this, but I got to say. When I look back, cause theCUBE gives us kind of early visibility. So companies with momentum and you talk to the customers that all these shows that we go to. I will tell you that three companies stood out last decade. It was Splunk. It was Service Now and Tableau. And you could tell just from just discussions with their customers, the enthusiasm in that customer base. And so that's a real asset, and that helps them build them a moat. So we'll see. All right, let's take a look at the same dimensions now for cyber. This is cybersecurity net score in the vertical, and market share in the horizontal. And I filtered by in greater than a hundred shared in because just gets so crowded. Erik, the only things I would point out here is CrowdStrike and Zscaler continue to shine, CyberArk also showing momentum over that 40% line. Very impressively, Palo Alto networks, which has a big presence in the market. They've bounced back. We predicted that a while back. Your round table suggested people like working with Palo Alto. They're a gold standard. You know, we had reported earlier on that divergence with four to net in terms of valuation and some of the challenges they had in cloud, clearly, you know, back with the momentum. And of course, Microsoft in the upper, right. It's just, they're literally off the charts and obviously a major player here, but your thoughts on cyber? >> Erik: Yeah. Going back to the backdrop. Security, security, security. It has been the number one priority going back to last September. No one sees it changing. It has to happen. The threat vectors are actually expanding and we have no choice but to spend here. So it is not surprising to see. You did name our three favorite names. So as you know, we look at the dataset, we see which ones have the most positive inflections, and we put outlooks on those. And you did mention Zscaler, Okta and CrowdStrike, by far the three standouts that we're seeing. I just recently did a huge panel on Okta talking about their acquisition of Auth Zero. They're pushed into Sale Point space, trying to move just from single sign on and MFA to going to really privileged account management. There is some hurdles there. Really Okta's ability to do this on-prem is something that a little bit of the IT end users are concerned about. But what we're seeing right now, both Okta and Auth Zero are two of the main adopted names in security. They look incredibly well set up. Zscaler as well. With the ZTNA push more towards zero trust, Zscaler came out so hot in their IPO. And everyone was wondering if it was going to trail off just like Snowflake. It's not trailing off. This thing just keeps going up into the right, up into the right. The data supports a lot of tremendous growth for the three names that you just mentioned. >> Yeah. Yeah. I'm glad you brought up Auth Zero. We had reported on that earlier. I just feel like that was a great acquisition. You had Okta doing the belly to belly enterprise, you know, selling. And the one thing that they really lacked was that developer momentum. And that's what Auth Zero brings. Just a smart move by Todd McKinnon and company. And I mean, so this, you know, I want to, I want to pull up another chart show a quick snapshot of some of the players in the survey who show momentum and have you comment on this. We haven't mentioned Snowflake so far, but they remain again with like this gold standard of net score, they've consistently had those high marks with regard to spending velocity. But here's some other data. Erik, how should we interpret this? >> Erik: Yeah, just to harp on Snowflake for a second. Right, I mean the rich get richer. They came out- IPO was so hyped, so it was hard for us as a research company to say, "Oh, you know, well, you know, we agree." But we did. The data is incredible. You can't beat the management team. You can't beat what they're doing. They've got so much cash. I can't wait to see what they do with it. And meanwhile, you would expect something that debuted with that high of a net score, that high of spending velocity to trail off. It would be natural. It's not Dave, it's still accelerating. It's gone even higher. It's at all time highs. And we just don't see it stopping anytime soon. It's a really interesting space right now. Maybe another name to look at on here that I think is pretty interesting, kind of a play on return to business is Kupa. It's a great project expense management tool that got hit really hard. Listen, traveling stopped, business expense stopped, and I did a panel on it. And a lot of our guys basically said, "Yeah, it was the first thing I cut." But we're seeing a huge rebound in spending there in that space. So that's a name that I think might be worth being called out on a positive side. Negative, If you look down to the bottom right of that chart, unfortunately we're seeing some issues in RingCentral and Zoom. Anything that's sort of playing in this next, you know, video conferencing, IP telephony space, they seem to be having really decelerating spending. Also now with Zoom's acquisition of five nine. I'm not really sure how RingCentral's going to compete on that. But yeah, that's one where we debuted for the first time with a negative outlook on that name. And looking and asking to some of the people in our community, a lot of them say externally, you still need IP telepany, but internally you don't. Because the You Cast communication systems are getting so sophisticated, that if I have Teams, if I have Slack, I don't need phones anymore. (chuckling) That you and I can just do a Slack call. We can do a Teams call. And many of them are saying I'm truly ripping out my IP Telepany internally as soon as possible because we just don't need it. So this whole collaboration, productivity space is here to stay. And it's got wide ranging implications to some of these more legacy type of tools. >> You know, one of the other things I'd call out on this chart is Accenture. You and I had a session earlier this year, and we had predicted that that skill shortage was going to lead to an uptick in traditional services. We've certainly seen that. I mean, IBM beat its quarter on the strength of services largely. And seeing Accenture on that is I think confirmation. >> Yeah that was our New Year prediction show, right Dave? When we made top 10 predictions? >> That's right. That was part of our predictions show. Exactly, good memory. >> The data is really showing that continue. People want the projects, they need to do the projects, but hiring is very difficult. So obviously the number one beneficiary there are going to be the Accentures of the world. >> All right. So let's do a quick wrap. I'm going to make a few comments and then have you bring us home, Erik. So we laid out our scenario for the tech spending rebound. We definitely believe last year tracked downward, along with GDP contraction. It was interesting. Gardner doesn't believe, at least factions of Gardner don't believe there's a correlation between GDP and tech spending. But, you know, I personally think there generally is some kind of relatively proportional pattern there. And I think we saw contraction last year. People are concerned about inflation. Of course, that adds some uncertainty. And as well, as you mentioned around the Delta variant. But I feel as though that the boards of directors and CEOs, they've mandated that tech execs have to build out digital platforms for the future. They're data centric. They're highly automated, to your earlier points. They're intelligent with AI infused, and that's going to take investment. I feel like the tech community has said, "Look, we know what to do here. We're dealing with hybrid work. We can't just stop doing what we're doing. Let's move forward." You know, and as you say, we're flying again and so forth. You know, getting hybrid right is a major priority that directly impacts strategies. Technology strategies, particularly around security, cloud, the productivity of remote workers with collaboration. And as we've said many times, we are entering a new era of data that's going to focus on decentralized data, building data products, and Erik let's keep an eye on this observability space. Lot of interest there, and buyers have a number of choices. You know, do they go with a specialist, as we saw recently, we've seen in the past, or did they go with the generalist like Service Now with the acquisition of LightStep? You know, it's going to be interesting. A lot of people are going to get into this space, start bundling into larger platforms. And so as you said, there's probably not enough room for all the players. We're going to see some consolidation there. But anyway, let me give you the final word here. >> Yeah, no, I completely agree with all of it. And I think your earlier points are spot on, that analytics and automation are certainly going to be moving more and more to that left of that chart we had of priorities. I think as we continue that survey heading into 2022, we'll have some fresh data for you again in a few months, that's going to start looking at 2022 priorities and overall spend. And the one other area that I keep hearing about over and over and over again is customer experience. There's a transition from good old CRM to CXM. Right now, everything is digital. It is not going away. So you need an omni-channel support to not only track your customer experience, but improve it. Make sure there's a two way communication. And it's a really interesting space. Salesforce is going to migrate into it. We've got Qualtrics out there. You've got Medallia. You've got FreshWorks, you've got Sprinkler. You got some names out there. And everyone I keep talking to on the IT end user side keeps bringing up customer experience. So let's keep an eye on that as well. >> That's a great point. And again, it brings me back to Service Now. We wrote a piece last week that's sort of, Service Now and Salesforce are on a collision course. We've said that for many, many years. And you've got this platform of platforms. They're just kind of sucking in different functions saying, "Hey, we're friends with everybody." But as you know Erik, software companies, they want to own it all. (both chuckling) All right. Hey Erik, thank you so much. I want to thank you for coming back on. It's always a pleasure to have you on Breaking Analysis. Great to see you. >> Love the partnership. Love the collaboration. Let's go enjoy this summer Friday. >> All right. Let's do. Okay, remember everybody, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast, click subscribe to the series. Check out ETR's website at etr.plus. They've just launched a new website. They've got a whole new pricing model. It's great to see that innovation going on. Now remember we also publish a full report every week on WikiBond.com and SiliconAngle.com. You can always email me, appreciate the back channel comments, the metadata insights. David.Vellante@SiliconAngle.com. DM me on Twitter @DVellante or comment on the LinkedIn posts. This is Dave Vellante for Erik Bradley and theCUBE insights powered by ETR. Have a great week, a good rest of summer, be well. And we'll see you next time. (inspiring music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante recent survey data from etr shows that enterprise tech spending is tracking with projected u.s gdp growth at six to seven percent this year many markers continue to point the way to a strong recovery including hiring trends and the loosening of frozen it project budgets however skills shortages are blocking progress at some companies which bodes well for an increased reliance on external i.t services moreover while there's much to talk about well there's much talk about the rotation out of work from home plays and stocks such as video conferencing vdi and other remote worker tech we see organizations still trying to figure out the ideal balance between funding headquarter investments that have been neglected and getting hybrid work right in particular the talent gap combined with a digital mandate means companies face some tough decisions as to how to fund the future while serving existing customers and transforming culturally hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome back eric porter bradley of etr who will share fresh data perspectives and insights from the latest survey data eric great to see you welcome thank you very much dave always good to see you and happy to be on the show again okay we're going to share some macro data and then we're going to dig into some highlights from etr's most recent march covid survey and also the latest april data so eric the first chart that we want to show it shows cio and it buyer responses to expected i.t spend for each quarter of 2021 versus 2020. and you can see here a steady quarterly improvement eric what are the key takeaways from your perspective sure well first of all for everyone out there this particular survey had a record-setting number of uh participation we had uh 1 500 i.t decision makers participate and we had over half of the fortune 500 and over a fifth of the global 1000. so it was a really good survey this is the seventh iteration of the covet impact survey specifically and this is going to transition to an over large macro survey going forward so we could continue it and you're 100 right what we've been tracking here since uh march of last year was how is spending being impacted because of covid where is it shifting and what we're seeing now finally is that there is a real re-acceleration in spend i know we've been a little bit more cautious than some of the other peers out there that just early on slapped an eight or a nine percent number but what we're seeing is right now it's at a midpoint of over six uh about six point seven percent and that is accelerating so uh we are still hopeful that that will continue uh really that spending is going to be in the second half of the year as you can see on the left part of this chart that we're looking at uh it was about 1.7 versus 3 for q1 spending year over year so that is starting to accelerate through the back half you know i think it's prudent to be be cautious relative because normally you'd say okay tech is going to grow a couple of points higher than gdp but it's it's really so hard to predict this year okay the next chart is here that we want to show you is we ask respondents to indicate what strategies they're employing in the short term as a result of coronavirus and you can see a few things that i'll call out and then i'll ask eric to chime in first there's been no meaningful change of course no surprise in tactics like remote work and halting travel however we're seeing very positive trends in other areas trending downward like hiring freezes and freezing i.t deployments downward trend in layoffs and we also see an increase in the acceleration of new i.t deployments and in hiring eric what are your key takeaways well first of all i think it's important to point out here that uh we're also capturing that people believe remote work productivity is still increasing now the trajectory might be coming down a little bit but that is really key i think to the backdrop of what's happening here so people have a perception that productivity of remote work is better than hybrid work and that's from the i.t decision makers themselves um but what we're seeing here is that uh most importantly these organizations are citing plans to increase hiring and that's something that i think is really important to point out it's showing a real thawing and to your point in right in the beginning of the intro uh we are seeing deployments stabilize versus prior survey levels which means early on they had no plans to launch new tech deployments then they said nope we're going to start and now that's stalling and i think it's exactly right what you said is there's an i.t skills shortage so people want to continue to do i.t deployments because they have to support work from home and a hybrid back return to the office but they just don't have the skills to do so and i think that's really probably the most important takeaway from this chart um is that stalling and to really ask why it's stalling yeah so we're going to get into that for sure and and i think that's a really key point is that that that accelerating it deployments is some it looks like it's hit a wall in the survey and so but before before we get deep into the skills let's let's take a look at this next chart and we're asking people here how a return to the new normal if you will and back to offices is going to change spending with on-prem architectures and applications and so the first two bars they're cloud-friendly if you add them up at 63 percent of the respondents say that either they'll stay in the cloud for the most part or they're going to lower the on-prem spend when they go back to the office the next three bars are on-prem friendly if you add those up as 29 percent of the respondents say their on-prem spend is going to bounce back to pre-covert levels or actually increase and of course 12 percent of that number by the way say they they've never altered their on-prem spend so eric no surprise but this bodes well for cloud but but it it isn't it also a positive for on-prem this we've had this dual funding premise meaning cloud continues to grow but neglected data center spend also gets a boost what's your thoughts you know really it's interesting it's people are spending on all fronts you and i were talking in a prep it's like you know we're we're in battle and i've got naval i've got you know air i've got land uh i've got to spend on cloud and digital transformation but i also have to spend for on-prem uh the hybrid work is here and it needs to be supported so this spending is going to increase you know when you look at this chart you're going to see though that roughly 36 percent of all respondents say that their spending is going to remain mostly on cloud so this you know that is still the clear direction uh digital transformation is still happening covid accelerated it greatly um you know you and i as journalists and researchers already know this is where the puck is going uh but spend has always lagged a little bit behind because it just takes some time to get there you know inversely 27 said that their on-prem spending will decrease so when you look at those two i still think that the trend is the friend for cloud spending uh even though yes they do have to continue spending on hybrid some of it's been neglected there are refresh cycles coming up so overall it just points to more and more spending right now it really does seem to be a very strong backdrop for it growth so i want to talk a little bit about the etr taxonomy before we bring up the next chart we get a lot of questions about this and of course when you do a massive survey like you're doing you have to have consistency for time series so you have to really think through what that what the buckets look like if you will so this next chart takes a look at the etr taxonomy and it breaks it down into simple to understand terms so the green is the portion of spending on a vendor's tech within a category that is accelerating and the red is the portion that is decelerating so eric what are the key messages in this data well first of all dave thank you so much for pointing that out we used to do uh just what we call a next a net score it's a proprietary formula that we use to determine the overall velocity of spending some people found it confusing um our data scientists decided to break this sector breakdown into what you said which is really more of a mode analysis in that sector how many of the vendors are increasing versus decreasing so again i just appreciate you bringing that up and allowing us to explain the the the reasoning behind our analysis there but what we're seeing here uh goes back to something you and i did last year when we did our predictions and that was that it services and consulting was going to have a true rebound in 2021 and that's what this is showing right here so in this chart you're going to see that consulting and services are really continuing their recovery uh 2020 had a lot of declines and they have the biggest sector over year-over-year acceleration sector-wise the other thing to point out in this which we'll get to again later is that the inverse analysis is true for video conferencing uh we will get to that so i'm going to leave a little bit of ammunition behind for that one but what we're seeing here is it consulting services being the real favorable and video conferencing uh having a little bit more trouble great okay and then let's let's take a look at that services piece and this next chart really is a drill down into that space and emphasizes eric what you were just talking about and we saw this in ibm's earnings where still more than 60 percent of ibm's business comes from services and the company beat earnings you know in part due to services outperforming expectations i think it had a somewhat easier compare and some of this pen-up demand that we've been talking about bodes well for ibm and in other services companies it's not just ibm right eric no it's not but again i'm going to point out that you and i did point out ibm in our in our predictions one we did in late december so it is nice to see one of the reasons we don't have a more favorable rating on ibm at the moment is because they are in the the process of spinning out uh this large unit and so there's a little bit of you know corporate action there that keeps us off on the sideline but i would also want to point out here uh tata infosys and cognizant because they're seeing year-over-year acceleration in both it consulting and outsourced i t services so we break those down separately and those are the three names that are seeing acceleration in both of those so again a tata emphasis and cognizant are all looking pretty well positioned as well so we've been talking a little bit about this skill shortage and this is what's i think so hard for for forecasters um is that you know on the one hand there's a lot of pent up demand you know it's like scott gottlieb said it's like woodstock coming out of the covid uh but on the other hand if you have a talent gap you've got to rely on external services so there's a learning curve there's a ramp up it's an external company and so it takes time to put those together so so this data that we're going to show you next uh is is really important in my view and ties what we're saying we're saying at the top it asks respondents to comment on their staffing plans the light blue is we're increasing staff the gray is no change in the magenta or whatever whatever color that is that sort of purplish color anyway that color is is decreasing and the picture is very positive across the board full-time staff offshoring contract employees outsourced professional services all up trending upwards and this eric is more evidence of the services bounce back yeah it certainly is david and what happened is when we caught this trend we decided to go one level deeper and say all right we're seeing this but we need to know why and that's what we always try to do here data will tell you what's happening it doesn't always tell you why and that's one of the things that etr really tries to dig in with through the insights interviews panels and also going direct with these more custom survey questions uh so in this instance i think the real takeaway is that 30 of the respondents said that their outsourced and managed services are going to increase over the next three months that's really powerful that's a large portion of organizations in a very short time period so we're capturing that this acceleration is happening right now and it will be happening in real time and i don't see it slowing down you and i are speaking about we have to you know increase cloud spend we have to increase hybrid spend there are refresh cycles coming up and there's just a real skill shortage so this is a long-term setup that bodes very well for it services and consulting you know eric when i came out of college i somebody told me read read read read as much as you can and and so i would and they said read the wall street journal every day and i so i did it and i would read the tech magazines and back then it was all paper and what happens is you begin to connect the dots and so the reason i bring that up is because i've now been had taken a bath in the etr data for the better part of two years and i'm beginning to be able to connect the dots you know the data is not always predictive but many many times it is and so this next data gets into the fun stuff where we name names a lot of times people don't like it because the marketing people and organizations say well the data's wrong of course that's the first thing they do is attack the data but you and i know we've made some really great calls work from home for sure you're talking about the services bounce back uh we certainly saw the rise of crowdstrike octa zscaler well before people were talking about that same thing with video conferencing and so so anyway this is the fun stuff and it looks at positive versus negative sentiment on on companies so first how does etr derive this data and how should we interpret it and what are some of your takeaways [Music] sure first of all how we derive the data or systematic um survey responses that we do on a quarterly basis and we standardize those responses to allow for time series analysis so we can do trend analysis as well we do find that our data because it's talking about forward-looking spending intentions is really more predictive because we're talking about things that might be happening six months three months in the future not things that a lot of other competitors and research peers are looking at things that already happened uh they're looking in the past etr really likes to look into the future and our surveys are set up to do so so thank you for that question it's an enjoyable lead-in but to get to the fun stuff like you said uh what we do here is we put ratings on the data sets i do want to put the caveat out there that our spending intentions really only captures top-line revenue it is not indicative of profit margin or any other line items so this is only going to be viewed as what we are rating the data set itself not the company um you know that's not what we're in the game of doing so i think that's very important for the marketing and the vendors out there themselves when they when they take a look at this we're just talking about what we can control which is our data we're going to talk about a few of the names here on this highlighted vendors list one we're going to go back to that you and i spoke about i guess about six months ago or maybe even earlier which was the observability space um you and i were noticing that it was getting very crowded a lot of new entrants um there was a lot of acquisition from more of the legacy or standard entrance players in the space and that is continuing so i think in a minute we're going to move into that observability space but what we're seeing there is that it's becoming incredibly crowded and we're possibly seeing signs of them cannibalizing each other uh we're also going to move on a little bit into video conferencing where we're capturing some spend deceleration and then ultimately we're going to get into a little bit of a storage refresh cycle and talk about that but yeah these are the highlighted vendors for april um we usually do this once a quarter and they do change based on the data but they're not usually whipsawed around the data doesn't move that quickly yeah so you can see the some of the big names on the left-hand side some of the sas companies that have momentum obviously servicenow has been doing very very well we've talked a lot about snowflake octa crowdstrike z scalar in all very positive as well as you know several others i i guess i'd add some some things i mean i think if thinking about the next decade it's it's cloud which is not going to be like the same cloud as last decade a lot of machine learning and deep learning and ai and the cloud is extending to the edge in the data center data obviously very important data is decentralized and distributed so data architectures are changing a lot of opportunities to connect across clouds and actually create abstraction layers and then something that we've been covering a lot is processor performance is actually accelerating relative to moore's law it's probably instead of doubling every two years it's quadrupling every two years and so that is a huge factor especially as it relates to powering ai and ai inferencing at the edge this is a whole new territory custom silicon is is really becoming in vogue uh and so we're something that we're watching very very closely yeah i completely completely agree on that and i do think that the the next version of cloud will be very different another thing to point out on that too is you can't do anything that you're talking about without collecting the data and and organizations are extremely serious about that now it seems it doesn't matter what industry they're in every company is a data company and that also bodes well for the storage call we do believe that there is going to just be a huge increase in the need for storage um and yes hopefully that'll become portable across multi-cloud and hybrid as well now as eric said the the etr data's it's it's really focused on that top line spend so if you look at the uh on on the right side of that chart you saw you know netapp was kind of negative was very negative right but there's a company that's in in transformation now they've lowered expectations and they've recently beat expectations that's why the stock has been doing better but but at the macro from a spending standpoint it's still challenged so you have big footprint companies like netapp and oracle is another one oracle's stock is at an all-time high but the spending relative to sort of previous cycles or relative to you know like for instance snowflake much much smaller not as high growth but they're managing expectations they're managing their transition they're managing profitability zoom is another one zoom looking looking negative but you know zoom's got to use its market cap now to to transform and increase its tam uh and then splunk is another one we're going to talk about splunk is in transition it acquired signal fx it just brought on this week teresa carlson who was the head of aws public sector she's the president and head of sales so they've got a go to market challenge and they brought in teresa carlson to really solve that but but splunk has been trending downward we called that you know several quarters ago eric and so i want to bring up the data on splunk and this is splunk eric in analytics and it's not trending in the right direction the green is accelerating span the red is and the bars is decelerating spend the top blue line is spending velocity or net score and the yellow line is market share or pervasiveness in the data set your thoughts yeah first i want to go back is a great point dave about our data versus a disconnect from an equity analysis perspective i used to be an equity analyst that is not what we do here and you you may the main word you said is expectations right stocks will trade on how they do compared to the expectations that are set uh whether that's buy side expectations sell side expectations or management's guidance themselves we have no business in tracking any of that what we are talking about is top line acceleration or deceleration so uh that was a great point to make and i do think it's an important one for all of our listeners out there now uh to move to splunk yes i've been capturing a lot of negative commentary on splunk even before the data turned so this has been about a year-long uh you know our analysis and review on this name and i'm dating myself here but i know you and i are both rock and roll fans so i'm gonna point out a led zeppelin song and movie and say that the song remains the same for splunk we are just seeing uh you know recent spending intentions are taking yet another step down both from prior survey levels from year ago levels uh this we're looking at in the analytics sector and spending intentions are decelerating across every single customer group if we went to one of our other slide analysis um on the etr plus platform and you do by customer sub sample in analytics it's dropping in every single vertical it doesn't matter which one uh it's really not looking good unfortunately and you had mentioned this as an analytics and i do believe the next slide is an information security yeah let's bring that up and it's unfortunately it's not doing much better so this is specifically fortune 500 accounts and information security uh you know there's deep pockets in the fortune 500 but from what we're hearing in all the insights and interviews and panels that i personally moderate for etr people are upset they didn't like the the strong tactics that splunk has used on them in the past they didn't like the ingestion model pricing the inflexibility and when alternatives came along people are willing to look at the alternatives and that's what we're seeing in both analytics and big data and also for their sim in security yeah so i think again i i point to teresa carlson she's got a big job but she's very capable she's gonna she's gonna meet with a lot of customers she's a go to market pro she's gonna have to listen hard and i think you're gonna you're gonna see some changes there um okay so there's more sorry there's more bad news on splunk so bring this up is is is net score for splunk in elastic accounts uh this is for analytics so there's 106 elastic accounts that uh in the data set that also have splunk and it's trending downward for splunk that's why it's green for elastic and eric the important call out from etr here is how splunk's performance in elastic accounts compares with its performance overall the elk stack which obviously elastic is a big part of that is causing pain for splunk as is data dog and you mentioned the pricing issue uh is it is it just well is it pricing in your assessment or is it more fundamental you know it's multi-level based on the commentary we get from our itdms that take the survey so yes you did a great job with this analysis what we're looking at is uh the spending within shared accounts so if i have splunk already how am i spending i'm sorry if i have elastic already how is my spending on splunk and what you're seeing here is it's down to about a 12 net score whereas splunk overall has a 32 net score among all of its customers so what you're seeing there is there is definitely a drain that's happening where elastic is draining spend from splunk and usage from them uh the reason we used elastic here is because all observabilities the whole sector seems to be decelerating splunk is decelerating the most but elastic is the only one that's actually showing resiliency so that's why we decided to choose these two but you pointed out yes it's also datadog datadog is cloud native uh they're more devops oriented they tend to be viewed as having technological lead as compared to splunk so that's a really good point a dynatrace also is expanding their abilities and splunk has been making a lot of acquisitions to push their cloud services they are also changing their pricing model right they're they're trying to make things a little bit more flexible moving off ingestion um and moving towards uh you know consumption so they are trying and the new hires you know i'm not gonna bet against them because the one thing that splunk has going for them is their market share in our survey they're still very well entrenched so they do have a lot of accounts they have their foothold so if they can find a way to make these changes then they you know will be able to change themselves but the one thing i got to say across the whole sector is competition is increasing and it does appear based on commentary and data that they're starting to cannibalize themselves it really seems pretty hard to get away from that and you know there are startups in the observability space too that are going to be you know even more disruptive i think i think i want to key on the pricing for a moment and i've been pretty vocal about this i think the the old sas pricing model where essentially you essentially lock in for a year or two years or three years pay up front or maybe pay quarterly if you're lucky that's a one-way street and i think it's it's a flawed model i like what snowflake's doing i like what datadog's doing look at what stripe is doing look what twilio is doing these are cons you mentioned it because it's consumption based pricing and if you've got a great product put it out there and you know damn the torpedoes and i think that is a game changer i i look at for instance hpe with green lake i look at dell with apex they're trying to mimic that model you know they're there and apply it to to infrastructure it's much harder with infrastructure because you got to deploy physical infrastructure but but that is a model that i think is going to change and i think all of the traditional sas pricing is going to is going to come under disruption over the next you know better part of the decades but anyway uh let's move on we've we've been covering the the apm space uh pretty extensively application performance management and this chart lines up some of the big players here comparing net score or spending momentum from the april 20th survey the gray is is um is sorry the the the gray is the april 20th survey the blue is jan 21 and the yellow is april 21. and not only are elastic and data dog doing well relative to splunk eric but everything is down from last year so this space as you point out is undergoing a transformation yeah the pressures are real and it's you know it's sort of that perfect storm where it's not only the data that's telling us that but also the direct feedback we get from the community uh pretty much all the interviews i do i've done a few panels specifically on this topic for anyone who wants to you know dive a little bit deeper we've had some experts talk about this space and there really is no denying that there is a deceleration in spend and it's happening because that spend is getting spread out among different vendors people are using you know a data dog for certain aspects they're using elastic where they can because it's cheaper they're using splunk because they have to but because it's so expensive they're cutting some of the things that they're putting into splunk which is dangerous particularly on the security side if i have to decide what to put in and whatnot that's not really the right way to have security hygiene um so you know this space is just getting crowded there's disruptive vendors coming from the emerging space as well and what you're seeing here is the only bit of positivity is elastic on a survey over survey basis with a slight slight uptick everywhere else year over year and survey over survey it's showing declines it's just hard to ignore and then you've got dynatrace who based on the the interviews you do in the venn you're you know one on one or one on five you know the private interviews that i've been invited to dynatrace gets very high scores uh for their road map you've got new relic which has been struggling you know financially but they've got a purpose built they've got a really good product and a purpose-built database just for this apm space and then of course you've got cisco with appd which is a strong business for them and then as you mentioned you've got startups coming in you've got chaos search which ed walsh is now running you know leave the data in place in aws and really interesting model honeycomb it's going to be really disruptive jeremy burton's company observed so this space is it's becoming jump ball yeah there's a great line that came out of one of them and that was that the lines are blurring it used to be that you knew exactly that app dynamics what they were doing it was apm only or it was logging and monitoring only and a lot of what i'm hearing from the itdm experts is that the lines are blurring amongst all of these names they all have functionality that kind of crosses over each other and the other interesting thing is it used to be application versus infrastructure monitoring but as you know infrastructure is becoming code more and more and more and as infrastructure becomes code there's really no difference between application and infrastructure monitoring so we're seeing a convergence and a blurring of the lines in this space which really doesn't bode well and a great point about new relic their tech gets good remarks uh i just don't know if their enterprise level service and sales is up to snuff right now um as one of my experts said a cto of a very large public online hospitality company essentially said that he would be shocked that within 18 months if all of these players are still uh standalone that there needs to be some m a or convergence in this space okay now we're going to call out some of the data that that really has jumped out to etr in the latest survey and some of the names that are getting the most queries from etr clients which are many of which are investor clients so let's start by having a look at one of the most important and prominent work from home names zoom uh let's let's look at this eric is the ride over for zoom oh i've been saying it for a little bit of a time now actually i do believe it is um i will get into it but again pointing out great dave uh the reason we're presenting today splunk elastic and zoom are they are the most viewed on the etr plus platform uh trailing behind that only slightly is f5 i decided not to bring f5 to the table today because we don't have a rating on the data set um so then i went one deep one below that and it's pure so the reason we're presenting these to you today is that these are the ones that our clients and our community are most interested in which is hopefully going to gain interest to your viewers as well so to get to zoom um yeah i call zoom the pandec pandemic bull market baby uh this was really just one that had a meteoric ride you look back january in 2020 the stock was at 60 and 10 months later it was like like 580. that's in 10 months um that's cooled down a little bit uh into the mid 300s and i believe that cooling down should continue and the reason why is because we are seeing a huge deceleration in our spending intentions uh they're hitting all-time lows it's really just a very ugly data set um more importantly than the spending intentions for the first time we're seeing customer growth in our survey flattened in the past we could we knew that the the deceleration and spend was happening but meanwhile their new customer growth was accelerating so it was kind of hard to really make any call based on that this is the first time we're seeing flattening customer growth trajectory and that uh in tandem with just dominance from microsoft in every sector they're involved in i don't care if it's ip telephony productivity apps or the core video conferencing microsoft is just dominating so there's really just no way to ignore this anymore the data and the commentary state that zoom is facing some headwinds well plus you've pointed out to me that a lot of your private conversations with buyers says that hey we're we're using the freebie version of zoom you know we're not paying them and so in that combined with teams i mean it's it's uh it's i think you know look zoom has to figure it out they they've got to they've got to figure out how to use their elevated market cap to transform and expand their tan um but let's let's move on here's the data on pure storage and we've highlighted a number of times this company is showing elevated spending intentions um pure announces earnings in in may ibm uh just announced storage what uh it was way down actually so sort of still pure more positive but i'll comment on a moment but what does this data tell you eric yeah you know right now we started seeing this data last survey in january and that was the first time we really went positive on the data set itself and it's just really uh continuing so we're seeing the strongest year-over-year acceleration in the entire survey um which is a really good spot to be pure is also a leading position in among its sector peers and the other thing that was pretty interesting from the data set is among all storage players pure has the highest positive public cloud correlation so what we can do is we can see which respondents are accelerating their public cloud spend and then cross-reference that with their storage spend and pure is best positioned so as you and i both know uh you know digital transformation cloud spending is increasing you need to be aligned with that and among all storage uh sector peers uh pure is best positioned in all of those in spending intentions and uh adoptions and also public cloud correlation so yet again just another really strong data set and i have an anecdote about why this might be happening because when i saw the date i started asking in my interviews what's going on here and there was one particular person he was a director of cloud operations for a very large public tech company now they have hybrid um but their data center is in colo so they don't own and build their own physical building he pointed out that doran kovid his company wanted to increase storage but he couldn't get into his colo center due to covert restrictions they weren't allowed you had so 250 000 square feet right but you're only allowed to have six people in there so it's pretty hard to get to your rack and get work done he said he would buy storage but then the cola would say hey you got to get it out of here it's not even allowed to sit here we don't want it in our facility so he has all this pent up demand in tandem with pent up demand we have a refresh cycle the ssd you know depreciation uh you know cycle is ending uh you know ssds are moving on and we're starting to see uh new technology in that space nvme sorry for technology increasing in that space so we have pent up demand and we have new technology and that's really leading to a refresh cycle and this particular itdm that i spoke to and many of his peers think this has a long tailwind that uh storage could be a good sector for some time to come that's really interesting thank you for that that extra metadata and i want to do a little deeper dive on on storage so here's a look at storage in the the industry in context and some of the competitive i mean it's been a tough market for the reasons that we've highlighted cloud has been eating away that flash headroom it used to be you'd buy storage to get you know more spindles and more performance and you were sort of forced to buy more flash gave more headroom but it's interesting what you're saying about the depreciation cycle so that's good news so etr combines just for people's benefit here combines primary and secondary storage into a single category so you have companies like pure and netapp which are really pure play you know primary storage companies largely in the sector along with veeam cohesity and rubric which are kind of secondary data or data protection so my my quick thoughts here are that pure is elevated and remains what i call the one-eyed man in the land of the blind but that's positive tailwinds there so that's good news rubric is very elevated but down it's a big it's big competitor cohesity is way off its highs and i have to say to me veeam is like the steady eddy consistent player here they just really continue to do well in the data protection business and and the highs are steady the lows are steady dell is also notable they've been struggling in storage their isg business which comprises service and storage it's been soft during covid and and during even you know this new product rollout so it's notable with this new mid-range they have in particular the uptick in dell this survey because dell so large a small uptick can be very good for dell hpe has a big announcement next month in storage so that might improve based on a product cycle of course the nimble brand continues to do well ibm as i said just announced a very soft quarter you know down double digits again uh and there in a product cycle shift and netapp is that looks bad in the etr data from a spending momentum standpoint but their management team is transforming the company into a cloud play which eric is why it was interesting that pure has the greatest momentum in in cloud accounts so that is sort of striking to me i would have thought it would be netapp so that's something that we want to pay attention to but i do like a lot of what netapp is doing uh and other than pure they're the only big kind of pure play in primary storage so long winded uh uh intro there eric but anything you'd add no actually i appreciate it was long winded i i'm going to be honest with you storage is not my uh my best sector as far as a researcher and analyst goes uh but i actually think a lot of what you said is spot on um you know we do capture a lot of large organizations spend uh we don't capture much mid and small so i think when you're talking about these large large players like netapp and um you know not looking so good all i would state is that we are capturing really big organizations spending attention so these are names that should be doing better to be quite honest uh in those accounts and you know at least according to our data we're not seeing it and it's long-term depression as you can see uh you know netapp now has a negative spending velocity in this analysis so you know i can go dig around a little bit more but right now the names that i'm hearing are pure cohesity uh um i'm hearing a little bit about hitachi trying to reinvent themselves in the space but you know i'll take a wait-and-see approach on that one but uh pure and cohesity are the ones i'm hearing a lot from our community so storage is transforming to cloud as a service you're seeing things like apex and in green lake from dell and hpe and container storage little so not really a lot of people paying attention to it but pure about a company called portworx which really specializes in container storage and there's many startups there they're trying to really change the way david flynn has a startup in that space he's the guy who started fusion i o so a lot a lot of transformations happening here okay i know it's been a long segment we have to summarize and then let me go through a summary and then i'll give you the last word eric so tech spending appears to be tracking us gdp at six to seven percent this talent shortage could be a blocker to accelerating i.t deployments and that's kind of good news actually for for services companies digital transformation you know it's it remains a priority and that bodes well not only for services but automation uipath went public this week we we profiled that you know extensively that went public last wednesday um organizations they've i said at the top face some tough decisions on how to allocate resources you know running the business growing the business transforming the business and we're seeing a bifurcation of spending and some residual effects on vendors and that remains a theme that we're watching eric your final thoughts yeah i'm going to go back quickly to just the overall macro spending because there's one thing i think is interesting to point out and we're seeing a real acceleration among mid and small so it seems like early on in the covid recovery or kovitz spending it was the deep pockets that moved first right fortune 500 knew they had to support remote work they started spending first round that in the fortune 500 we're only seeing about five percent spent but when you get into mid and small organizations that's creeping up to eight nine so i just think it's important to point out that they're playing catch-up right now uh also would point out that this is heavily skewed to north america spending we're seeing laggards in emea they just don't seem to be spending as much they're in a very different place in their recovery and uh you know i do think that it's important to point that out um lastly i also want to mention i know you do such a great job on following a lot of the disruptive vendors that you just pointed out pure doing container storage we also have another bi-annual survey that we do called emerging technology and that's for the private names that's going to be launching in may for everyone out there who's interested in not only the disruptive vendors but also private equity players uh keep an eye out for that we do that twice a year and that's growing in its respondents as well and then lastly one comment because you mentioned the uipath ipo it was really hard for us to sit on the sidelines and not put some sort of rating on their data set but ultimately um the data was muted unfortunately and when you're seeing this kind of hype into an ipo like we saw with snowflake the data was resoundingly strong we had no choice but to listen to what the data said for snowflake despite the hype um we didn't see that for uipath and we wanted to and i'm not making a large call there but i do think it's interesting to juxtapose the two that when snowflake was heading to its ipo the data was resoundingly positive and for uipath we just didn't see that thank you for that and eric thanks for coming on today it's really a pleasure to have you and uh so really appreciate the the uh collaboration and look forward to doing more of these we enjoy the partnership greatly dave we're very very happy to have you in the etr family and looking forward to doing a lot lot more with you in the future ditto okay that's it for today remember these episodes are all available as podcasts wherever you listen all you got to do is search breaking analysis podcast and please subscribe to the series check out etr's website it's etr dot plus we also publish a full report every week on wikibon.com at siliconangle.com you can email me david.velante at siliconangle.com you can dm me on twitter at dvalante or comment on our linkedin post i could see you in clubhouse this is dave vellante for eric porter bradley for the cube insights powered by etr have a great week stay safe be well and we'll see you next time