(upbeat music) >> Good Friday morning everyone from Motor City, Lisa Martin here with John Furrier. This is our third day, theCUBE's third day of coverage of KubeCon + CloudNativeCon 22' North America. John, we've had some amazing conversations the last three days. We've had some good conversations about observability. We're going to take that one step further and look beyond its three pillars. >> Yeah, this is going to be a great segment. Looking forward to this. This is about in depth conversation on observability. The guest is technical and it's on the front lines with customers. Looking forward to this segment. Should be great. >> Yeah. Ian Smith is here, the field CTO at Chronosphere. Ian, welcome to theCUBE. Great to have you. >> Thank you so much. It's great to be here. >> All right. Talk about the traditional three pillars, approach, and observability. What are some of the challenges with that, and how does Chronosphere solve those? >> Sure. So hopefully everyone knows people think of the three pillars as logs, metrics and traces. What do you do with that? There's no action there. It's just data, right? You collect this data, you go put it somewhere, but it's not actually talking about any sort of outcomes. And I think that's really the heart of the issue, is you're not achieving anything. You're just collecting a whole bunch of data. Where do you put it? What are you... What can you do with it? Those are the fundamental questions. And so one of the things that we're focused on at Chronosphere is, well, what are those outcomes? What is the real value of that? And for example, thinking about phases of observability. When you have an incident or you're trying to investigate something through observability, you probably want to know what's going on. You want to triage any problems you detect. And then finally, you want to understand the cause of those and be able to take longer term steps to address them. >> What do customers do when they start thinking about it? Because observability has that promise. Hey, you know, get the data, we'll throw AI at it. >> Ian: Yeah. >> And that'll solve the problem. When they get over their skis, when do they realize that they're really not tackling it properly, or the ones that are taking the right approach? What's the revelation? What's your take on that? You're in the front lines. What's going on with the customer? The good and the bad. What's the scene look like? >> Yeah, so I think the bad is, you know, you end up buying a lot of things or implementing even in open source or self building, and it's very disconnected. You're not... You don't have a workflow, you don't have a path to success. If you ask different teams, like how do you address these particular problems? They're going to give you a bunch of different answers. And then if you ask about what their success rate is, it's probably very uneven. Another key indicator of problems is that, well, do you always need particular senior engineers in your instance or to help answer particular performance problems? And it's a massive anti pattern, right? You have your senior engineers who are probably need to be focused on innovation and competitive differentiation, but then they become the bottleneck. And you have this massive sort of wedge of maybe less experienced engineers, but no less valuable in the overall company perspective, who aren't effective at being able to address these problems because the tooling isn't right, the workflows are incorrect. >> So the senior engineers are getting pulled in to kind of fix and troubleshoot or observe what the observability data did or didn't deliver. >> Correct. Yeah. And you know, the promise of observability, a lot of people talk about unknown unknowns and there's a lot of, you know, crafting complex queries and all this other things. It's a very romantic sort of deep dive approach. But realistically, you need to make it very accessible. If you're relying on complex query languages and the required knowledge about the architecture and everything every other team is doing, that knowledge is going to be super concentrated in just a couple of heads. And those heads shouldn't be woken up every time at 3:00 AM. They shouldn't be on every instant call. But oftentimes they are the sort of linchpin to addressing, oh, as a business we need to be up 99.99% of the time. So how do we accomplish that? Well, we're going to end up burning those people. >> Lisa: Yeah. >> But also it leads to a great dissatisfaction in the bulk of the engineers who are, you know, just trying to build and operate the services. >> So talk... You mentioned that some of the problems with the traditional three pillars are, it's not outcome based, it leads to silo approaches. What is Chronosphere's definition and can you walk us through those three phases and how that really gives you that competitive edge in the market? >> Yeah, so the three phases being know, triage and understand. So just knowing about a problem, and you can relate this very specifically to capabilities, but it's not capabilities first, not feature function first. So know, I need to be able to alert on things. So I do need to collect data that gives me those signals. But particularly as you know, the industry starts moving towards as slows. You start getting more business relevant data. Everyone knows about alert storms. And as you mentioned, you know, there's this great white hope of AI and machine learning, but AI machine learning is putting a trust in sort of a black box, or the more likely reality is that really statistical model. And you have to go and spend a very significant amount time programming it for sort of not great outcomes. So know, okay, I want to know that I have a problem, I want to maybe understand the symptoms of that particular problem. And then triage, okay, maybe I have a lot of things going wrong at the same time, but I need to be very precise about my resources. I need to be able to understand the scope and importance. Maybe I have five major SLOs being violated right now. Which one is the greatest business impact? Which symptoms are impacting my most valuable customers? And then from there, not getting into the situation, which is very common where, okay, well we have every... Your customer facing engineering team, they have to be on the call. So we have 15 customer facing web services. They all have to be on that call. Triage is that really important aspect of really mitigating the cost to the organization because everyone goes, oh, well I achieved my MTTR and my experience from a variety of vendors is that most organizations, unless you're essentially failing as a business, you achieve your SLA, you know, three nines, four nines, whatever it is. But the cost of doing that becomes incredibly extreme. >> This is huge point. I want to dig into that if you don't mind, 'cause you know, we've been all seeing the cost of ownership miles in it all, the cost of doing business, cost of the shark fan, the iceberg, what's under the water, all those metaphors. >> Ian: Yeah. >> When you look at what you're talking about here, there are actually, actually real hardcore costs that might be under the water, so to speak, like labor, senior engineering time, 'cause Cloud Native engineers are coding in the pipelines. A lot of impact. Can you quantify and just share an example or illustrate where the costs are? 'Cause this is something that's kind of not obvious. >> Ian: Yeah. >> On the hard costs. It's not like a dollar amount, but time resource breach, wrong triage, gap in the data. What are some of the costs? >> Yeah, and I think they're actually far more important than the hard costs of infrastructure and licensing. And of course there are many organizations out there using open source observability components together. And they go, Oh it's free. No licensing costs. But you think again about those outcomes. Okay, I have these 15 teams and okay, I have X number of incidents a month, if I pull a representative from every single one of those teams on. And it turns out that, you know, as we get down in further phases, we need to be able to understand and remediate the issue. But actually only two teams required of that. There's 13 individuals who do not need to be on the call. Okay, yes, I met my SLA and MTTR, but if I am from a competitive standpoint, I'm comparing myself to a very similar organization that only need to impact those two engineers versus the 15 that I had over here. Who is going to be the most competitive? Who's going to be most differentiated? And it's not just in terms of number of lines of code, but leading to burnout of your engineers and the churn of that VPs of engineering, particularly in today's economy, the hardest thing to do is acquire engineers and retain them. So why do you want to burn them unnecessarily on when you can say, okay, well I can achieve the same or better result if I think more clearly about my observability, but reduce the number of people involved, reduce the number of, you know, senior engineers involved, and ultimately have those resources more focused on innovation. >> You know, one thing I want, at least want get in there, but one thing that's come up a lot this year, more than I've ever seen before, we've heard about the skill gaps, obviously, but burnout is huge. >> Ian: Yes. >> That's coming up more and more. This is a real... This actually doesn't help the skills gap either. >> Ian: Correct. >> Because you got skills gap, that's a cost potentially. >> Ian: Yeah. >> And then you got burnout. >> Ian: Yeah. >> People just kind of sitting on their hands or just walking away. >> Yeah. So one of the things that we're doing with Chronosphere is, you know, while we do deal with the, you know, the pillar data, but we're thinking about it more, what can you achieve with that? Right? So, and aligning with the know, triage and understand. And so you think about things like alerts, you know, dashboards, you be able to start triaging your symptoms. But really importantly, how do we bring the capabilities of things like distributed tracing where they can actually impact this? And it's not just in the context of, well, what can we do in this one incident? So there may be scenarios where you, absolutely do need those power users or those really sophisticated engineers. But from a product challenge perspective, what I'm personally really excited about is how do you capture that insight and those capabilities and then feed that back in from a product perspective so it's accessible. So you know, everyone talks about unknown unknowns in observability and then everyone sort of is a little dismissive of monitoring, but monitoring that thing, that democratizes access and the decision making capacity. So if you say I once worked at an organization and there were three engineers in the whole company who could generate the list of customers who were impacted by a particular incident. And I was in post sales at the time. So anytime there was a major incident, need to go generate that list. Those three engineers were on every single incident until one of them got frustrated and built a tool. But he built it entirely on his own. But can you think from an observability perspective, can you build a thing that it makes all those kinds of capabilities accessible to the first point where you take that alert, you know, which customers are affected or whatever other context was useful last time, but took an hour, two hours to achieve. And so that's what really makes a dramatic difference over time, is it's not about the day one experience, but how does the product evolve with the requirements and the workflow- >> And Cloud Native engineers, they're coding so they can actually be reactive. That's interesting, a platform and a tool. >> Ian: Yes. >> And platform engineering is the hottest topic at this event. And this year, I would say with Cloud Native hearing a lot more. I mean, I think that comes from the fact that SREs not really SRE, I think it's more a platform engineer. >> Ian: Yes. >> Not everyone's an... Not company has an SRE or SRE environment. But platform engineering is becoming that new layer that enables the developers. >> Ian: Correct. >> This is what you're talking about. >> Yeah. And there's lots of different labels for it, but I think organizations that really think about it well they're thinking about things like those teams, that developer efficiency, developer productivity. Because again, it's about the outcomes. It's not, oh, we just need to keep the site reliable. Yes, you can do that, but as we talked about, there are many different ways that you can burn unnecessary resources. But if you focus on developer efficiency and productivity, there's retainment, there's that competitive differentiation. >> Let's uplevel those business outcomes. Obviously you talked about in three phases, know, triage and understand. You've got great alignment with the Cloud Native engineers, the end users. Imagine that you're facilitating company's ability to reduce churn, attract more talent, retain talent. But what are some of the business outcomes? Like to the customer experience to the brand? >> Ian: Sure. >> Talk about it in some of those contexts. >> Yeah. One of the things that not a lot of organizations think about is, what is the reliability of my observability solution? It's like, well, that's not what I'm focused on. I'm focused on the reliability of my own website. Okay, let's take the, common open source pattern. I'm going to deploy my observability solution next to my core site infrastructure. Okay, I now have a platform problem because DNS stopped working in cloud provider of my choice. It's also affecting my observability solution. So at the moment that I need- >> And the tool chain and everything else. >> Yeah. At the moment that I need it the most to understand what's going on and to be able to know triage and understand that fails me at the same time. It's like, so reliability has this very big impact. So being able to make sure that my solution's reliable so that when I need it the most, and I can affect reliability of my own solution, my own SLA. That's a really key aspect of it. One of the things though that we, look at is it's not just about the outcomes and the value, it's ROI, right? It's what are you investing to put into that? So we've talked a little bit about the engineering cost, there's the infrastructure cost, but there's also a massive data explosion, particularly with Cloud Native. >> Yes. Give us... Alright, put that into real world examples. A customer that you think really articulates the value of what Chronosphere is delivering and why you're different in the market. >> Yeah, so DoorDash is a great customer example. They're here at KubeCon talking about their experience with Chronosphere and you know, the Cloud Native technologies, Prometheus and those other components align with Chronosphere. But being able to undergo, you know, a transformation, they're a Cloud Native organization, but going a transformation from StatsD to very heavy microservices, very heavy Kubernetes and orchestration. And doing that with your massive explosion, particularly during the last couple of years, obviously that's had a very positive impact on their business. But being able to do that in a cost effective way, right? One of the dirty little secrets about observability in particular is your business growth might be, let's say 50%, 60%, your infrastructure spend in the cloud providers is maybe going to be another 10, 15% on top of that. But then you have the intersection of, well my engineers need more data to diagnose things. The business needs more data to understand what's going on. Plus we've had this massive explosion of containers and everything like that. So oftentimes your business growth is going to be more than doubled with your observability data growth and SaaS solutions and even your on-premises solutions. What's the main cost driver? It's the volume of data that you're processing and storing. And so Chronosphere one of the key things that we do, because we're focused on organizational pain for larger scale organizations, is well, how do we extract the maximum volume of the data you're generating without having to store all of that data and then present it not just from a cost perspective, but also from a performance perspective. >> Yes. >> John: Yeah. >> And so feeding all into developer productivity and also lowering that investment so that your return can stand out more clearly and more valuably when you are assessing that TCO. >> Better insights and outcomes drives developer productivity for sure. That also has top theme here at KubeCon this year. It always is, but this is more than ever 'cause of the velocity. My question for you, given that you're the field chief technology officer for Chronosphere and you have a unique position, you've got a great experience in the industry, been involved in some really big companies and cutting edge. What's the competitive landscape? 'Cause the customers sometimes are confused by all the pitches they're getting from other vendors. Some are bolting on observability. Some have created like I would say, a shim layer or horizontally scalable platform or platform engineering approach. It's a data problem. Okay. This is a data architecture challenge. You mentioned that many times. What's the difference between a pretender and a player in this space? What's the winning architecture look like? What's a, I won't say phony or fake solution, but ones that customers should be aware of? Because my opinion, if you have a gap in the data or you configure it wrong, like a bolt on and say DNS crashes you're dead in the water. >> Ian: Yeah. >> What's the right approach from a customer standpoint? How do they squint through all the noise to figure out what's the right approach? >> Yeah, so I mean, I think one of the ways, and I've worked with customers in a pre-sales capacity for a very long time I know all the tricks of guiding you through. I think it needs to be very clear that customers should not be guided by the vendor. You don't talk to one vendor and they decide, Oh, I'm going to evaluate based off this. We need to particularly get away from feature based evaluations. Features are very important, but they're all have to be aligned around outcomes. And then you have to clearly understand, where am I today? What do I do today? And what is going to be the transformation that I have to go through to take advantage of these features? They can get very entrancing to say, Oh, there's a list of 25 features that this solution has that no one else has, but how am I going to get value out of that? >> I mean, distributed tracing is a distributed word. Distributed is the key word. This is a system architecture. The holistic big picture comes in. How do they figure that out? Knowing what they're transforming into? How does it fit in? >> Ian: Yeah. >> What's the right approach? >> Too often I say distributed tracing, particularly, you know, bought, because again, look at the shiny features look at the the premise and the MTTR expectations, all these other things. And then it's off to the side. We go through the traditional usage of metrics very often, very log heavy approaches, maybe even some legacy APM. And then it's sort of at last resort. And out of all the tools, I think distributed tracing is the worst in the problem we talked about earlier where the most sophisticated engineers, the ones who are being longest tenured, are the only ones who end up using it. So adoption is really, really poor. So again, what do we do today? Well, we alert, we probably want to understand our symptoms, but then what is the key problem? Oh, we spend a lot of time digging into the where the problem exists in my architecture, we talked about, you know, getting every engineer in at the same time, but how do we reduce the number of engineers involved? How do we make it so that, well, this looks like a great day one experience, but what is my day 30 experience like? Day 90. How is the product get more valuable? How do I get my most senior engineers out of this, not just on day one, but as we progress through it? >> You got to operationalize it. That's the key. >> Yeah, Correct. >> Summarize this as we wrap here. When you're in customer conversations, what is the key factor behind Chronosphere's success? If you can boil it down to that key nugget, what is it? >> I think the key nugget is that we're not just fixated on sort of like technical features and functions and frankly gimmicks of like, Oh, what could you possibly do with these three pillars of data? It's more about what can we do to solve organizational pain at the high level? You know, things like what is the cost of these solutions? But then also on the individual level, it's like, what exactly is an engineer trying to do? And how is their quality of life affected by this kind of tooling? And it's something I'm very passionate about. >> Sounds like it. Well, the quality of life's important, right? For everybody, for the business, and ultimately ends up affecting the overall customer experience. So great job, Ian, thank you so much for joining John and me talking about what you guys are doing beyond the three pillars of observability at Chronosphere. We appreciate your insights. >> Thank you so much. >> John: All right. >> All right. For John Furrier and our guest, I'm Lisa Martin. You're watching theCUBE live Friday morning from KubeCon + CloudNativeCon 22' from Detroit. Our next guest joins theCUBE momentarily, so stick around. (upbeat music)

>>Good afternoon everyone, and welcome back to Cuan where my cohost John Farer and I are broadcasting live, along with Lisa Martin from Cuan Detroit, Michigan. We are joined this afternoon by two very interesting gentlemen who also happen to be legends on the cube. John, how long have you known the next few? They've, >>They've made their mark on the cube with Jerry Chen from Greylock was one of our most attended cube guests. He's a VC partner at Greylock and an investor and this company that just launched their new cloud observability platform should be a great segment. >>Well, I'm excited. I are. Are you excited? Should I string this out just a little bit longer? No, I won't. I won't do that to you. Please welcome Martin and Jeff from Chronosphere Martin. Jeff, thank you so much for being >>Here. Thank you for having us. Thank you. >>I noticed right away that you have raised a mammoth series C. Yeah. 200 million if I'm not mistaken. >>That is correct. >>Where's the company at? >>Yeah, so we raised that series C a year ago. In fact, we were just talking about it a year ago at Cub Con. Since then, at the time we're about 80 employees or so. Since then, we've tripled the headcount, so we're over 200 people. Casual, triple casual, triple of the headcount. Yeah. Luckily it was the support of business, which is also tripled in the last year. So we're very lucky from that perspective as well. And a couple of other things we're pretty proud of last year. We've had a hundred percent customer retention, which is always a great thing to have as a SaaS platform there. >>Real metric if you've had a hundred percent. I'm >>Kidding. It's a good metric to, to put out there if you had a hundred percent. I would say for sure. It's an A for sure and exactly welcome to meet >>Anyone else who's had a hundred percent >>Customer attention here at coupon this week and 90% of our customers are using more of the service and, and you know, therefore paying more for the service as well. So those are great science for us and I think it shows that we're clearly doing something right on the product side. I would say. And >>Last and last time you're on the cube. We're talking about about the right data. Not so much a lot of data, if I remember correctly. Yeah, a hundred percent. And that was a unique approach. Yeah, it's a data world on relative observability. And you guys just launched a new release of your platform, cloud native platform. What's new in the platform? Can you share an update on what you guys release? >>Yeah, well we did and, and you, you bring up a great point. You know, like it's not just in observably but overall data is exploding. Alright, so three things there. It's like, hey, can your platform even handle the explosion of data? Can it control it over time and make sure that as your business grows, the data doesn't continue explode at the same time. And then for the end users, can they make sense of all this data? Cuz what's the point of having it if the end users can't make sense of it? So actually our product announcement this time is a pretty big refresh of, of a lot of features in our, in our platform. And it actually tackles all three of these particular components. And I'll let Jeff, our head of product, Doug, >>You, you run product, you get the keys to the kingdom, I do product roadmap. People saying, Hey this, take this out. You're under a lot of pressure. What makes the platform platform a great observability product? >>So the keystone of what we do that's different is helping you control the data, right? As we're talking about there's an infinite amount of data. These systems are getting more and more and more complicated. A lot of what we do is help you understand the utility of the telemetry so that you can optimize for keeping and storing and paying for the data that's actually helpful as opposed to the stuff that isn't. >>What's the benefit now with observability, with all the noise out in the marketplace, there's been a shift over the past couple years. Cloud native at scale, you're seeing a lot more automation, almost a set to support the growth for more application development. We had a Docker CEO on earlier today, he said there are more applications being deployed in the past year than in the history of open source. So more and more apps are being deployed, more data's being generated. What's the key to observability right now that's gonna separate the winners from the losers? >>Yeah, I think, you know, not only are there more applications being deployed, but there are smaller and small applications being deployed mostly on containers these days more than if they, hence this conference gets larger and larger every year. Right? So, you know, I think the key is a can your system handle this data explosion is, is the first thing. Not only can it handle the data explosion, but you know, APM solutions have been around for a very long time and those were really introspecting into an application. Whereas these days what's more important is, well how is your application interfacing with every other application in your distributed architecture there, right? So the use case is slightly different there. And then to what Jeff was saying is like once the data is there, not only making use of what is actually useful to you, but then having the end user make sense of it. >>Because we, we, we always think about the technology changes. We forget that the end users are different now we used to have IT operations team operating everything and the developers would write the application, just throw it over the wall. These days the developers have to actually operate this thing in production. So the end users of these systems are very different as well. And you can imagine these are folks, your average developer as maybe not operated things for many years in production before. So they need to, that they need to pick up a new skill set, they need to use new tooling in order to, to do that. So yeah, it's, it's, >>And you got the developer persona, you got a developer that's building products for builders and developers that are building products to be consumed. So they're not, they're not really infrastructure builders, they're just app developers. >>Exactly. Exactly. That's right. And that's what a lot of the new functionality that we're introducing here at the show is all about is helping developers who build software by day and are on call by night, actually get in context. There's so much data chances of when that, when one of those pages goes off and your number comes up, that the problem happens to be in the part of the system that you know a lot about are pretty low, chances are you're gonna get bothered about something else. So we've built a feature, we call it collections that's about putting you in the right context and connecting you into the piece of the system where the problem is to orient you and to get you started. So instead of waiting through, through hundreds of millions of things, you're waiting through the stuff that's in the immediate neighborhood of where the >>Problem is. Yeah. To your point about data, you can't let it go unchecked. That's right. You gotta gotta understand that. And we were talking about containers again with, again with docker, you know, nuance point, but oh, scan your container. But not everyone's scanning the containers security nightmare, right? I mean, >>Well I think one of the things that I, I loved in reading the notes in preparation for you coming up is you've actually created cloud native observability with the goal of eliminating engineering burnout. And what you're talking about there is actually the cognitive burden of when things happen. Yeah, for sure. We we're, you know, we're not just designing for when everything goes right, You need to be prepared for when everything goes wrong and that poor lonely individual in the middle of the night has, it's >>A tough job. >>Has to navigate that >>And, and observability is just one thing you gotta mean like security is another thing. So, so many more things have been piled on top of the developer in addition to actually creating the application. Right? It is. There is a lot. And you know, observably is one of those key things you need to do your job. So as much as, as much as we can make that easier, that's a better bit. Like there are so many things being piled on right now. >>That's the holy grail right there. Because they don't want to be doing exactly >>The work. Exactly. They're not observability experts. >>Exactly. And automating that in. So where do you guys weigh in on the automation wave? Everything's automation. Yeah. Is that kind of a hand waving or what's going on? What's the reality? What's actually happening? >>Yeah, I think automation I think is key. You hear a lot of ai ml ops there. I, I don't know if I really believe in that or having a machine self heal itself or anything like that. But I think automation is key because there are a lot of repeatable tasks in a lot of what you're doing. So once you detect that something goes wrong, generally if you've seen it before, you know what the fix is. So I think automation plays a key on the sense that once it's detected again the second time, the third time, okay, I know what I did the previous time, let, let's make sure we can do that again. So automation I think is key. I think it helps a lot with the burnout. I dunno if I'd go as far as the >>Same burnout's a big deal. >>Well there's an example again in the, in the stuff we're releasing this week, a new feature we call query accelerator. That's a form of automation. Problem is you got all this data, mountain of data, put you in the right context so you're at least in the right neighborhood, but now you need to query it. You gotta get the data to actually inform the specific problem you're trying to solve. And the burden on the developer in that situation is really high. You have to know what you're looking for and you have to know how to efficiently ask for it. So you're not waiting for a long time and >>We >>Built a feature, you tell us what you want, we will figure out how to get it for you efficiently. That's the kind of automation that we're focused on. That's actually a good service. How can we, it >>Sounds >>Blissful. How can we accelerate and optimize what you were gonna do anyway, rather than trying to read your mind or predict the future. >>Yes, >>Savannah, some community forward. Yeah, I, I'm, so I'm curious, you, you clearly lead with a lot of empathy, both of you and, and putting your, well you probably have experience with this as well, but putting your mind or putting yourself in the mind to the developer are, what's that like for you from a product development standpoint? Are you doing a lot of community engagement? Are you talking to developers to try and anticipate what they're gonna be needing next in terms of, of your offering? Or how has that work >>For you? Oh, for sure. So, so I run product, I have a lot of product managers who work for me. Somebody that I used to work with, she was accusing me, but what she called, she called me an anthropologist of a product manager. I >>Get these kind of you, the very good design school vibes from you both of you, which >>Is, and the reason why she said the way you do this, you go and you live with them in order to figure out what a day in their life is really like, what the job is really like, what's easy, what's hard. And that's what we try to aim at and try to optimize for. So that's very much the way that we do all of >>Our work. And that's really also highlights the fact that we're in a market that requires acute realtime data from the customer. Cause it's, and it's all new data. Well >>Yeah, it's all changing. The tools change every day. I mean if we're not watching how, and >>So to your point, you need it in real time as well. The whole point of moving to cloud native is you have a reliable product or service there. And like if you need to wait a few minutes to even know that something's wrong, like you've already lost at that point, you've already lost a ton of customers, potentially. You've already lost a ton of business. You know, to your point about the, the community earlier, one other thing we're trying to do is also give back to the community a little bit. So actually two days ago we just announced the open source of a tool that we've been using in our product for a very long time. But of course our product is, is a paid product, right? But actually open source a part of that tool thus that the broader community can benefit as well. And that tool which, which tool is that? It's, it's called Prom lens. And it's actually the Prometheus project is the open sourced metrics project that everybody uses. So this is a query builder that helps developers understand how to create queries in a much more efficient way. We've had in our product for a long time, but we're like, let's give that back to the community so that the broader community of developers out there can have a much easier time creating these queries as well. What's >>Been the feedback? >>We only now it's two days ago so I'm not, I'm not exactly sure. I imagine >>It's great. They're probably playing with it right now. >>Exactly. Exactly. Exactly. For sure. I imagine. Great. >>Yeah, you guys mentioned burnout before and we heard this a lot now you mentioned in terms of data we've been hearing and reporting about Insta security world, which is also data specific observability ties right into security. Yep. How does a company figure out, first of all, burnout's a big problem. It's more and more data coming. It's like, it's like doesn't stop and the breaches are coming too. How does a company know when they need that their observability strategy is broken? Is there sig signs of you know, burnout? Is there signs of breaches? I mean, what are some of the tell signs that if I'm a CSO I go, you know what, maybe I should check out promisee. When do, when do you guys match in and go we're a perfect fit to solve that problem? >>Yeah, I, I would say, you know, because we're focused on the observability side, less so on the security side, some of those signals are like how many incidents do you have? How many outages do you have? What's the occurrence of these things and how long does it take to recover from from from these particular incidents? How >>Upsetting are we finding customers? >>Upsetting are >>Customer. Exactly. >>And and one trend was seeing >>Not churn happening. Exactly. >>And one trend we're seeing in the industry is that 68% of companies are saying that they're having more incidents over time. Right. And if you have more incidents, you can imagine more engineers are being paid, are being woken up and they're being put under more stress. And one thing you said that very interesting is, you know, I think generally in the observability world, you ideally actually don't want to figure out the problem when it goes wrong. Ideally what you want to do these days is figure out how do I remediate this and get the business back to a running state as quickly as I can. And then when the business isn't burning, let me go and figure out what the underlying root cause is. So the strategy there is changed as well from the APM days where like I don't want to figure out the problem in real time. I wanna make sure my business and my service is running as it should be. And then separately from that, once it is then I wanna go >>Under understand that assume it's gonna happen, be ready to close that isolate >>The >>Fire. Exactly. Exactly. And, and you know, you can imagine, you know the whole movement towards C I C D, like generally when you don't touch a system, nothing goes wrong. You deploy change, first thing you do is not figure out why you change break thing. Get that back like underplay that change roll that change back, get your business back to a estate and then take the time where you're not under pressure, you're not gonna be burnt out to figure out what was it about my change that that broke everything. So, yeah. Got >>It. >>Well it's not surprising that you've added some new exciting customers to the roster. We have. We have. You want to tell the audience who they might >>Be? Yes. It's been a few big names in the last year we're pretty excited about. One is Snapchat, I think everybody knows, knows that application And one is Robin Hood. So you know, you can imagine very large, I'll say tech forward companies that have completed their migrations to, to cloud native or a wallet on their way to Cloudnative and, and we like helping those customers for sure. We also like helping a lot of startups out there cause they start off in the cloud native world. Like if you're gonna build a business today, you're gonna use Kubernetes from day one. Right? But we're actually interestingly seeing more and more of is traditional enterprises who are just early, pretty early on in their cloudnative migration then now starting to adopt cloud native at scale and now they're running to the same problems. As well >>Said, the Gartner data last year was something like 85% of companies had not made that transformation. Right. So, and that, I mean that's looking at larger scale companies, obviously >>A hundred, you're >>Right on the pulse. They >>Have finished it, but a lot of them are starting it now. So we're seeing pilot >>Projects, testing and cadence. And I imagine it's a bit of a different pace when you're working with some of those transforming companies versus those startups that are, are just getting rolling. I >>Love and you know, you have a lot of legacy use case you have to, like, if you're a startup, you can imagine there's no baggage, there's no legacy. You're just starting brand new, right? If you're a large enterprise, you have to really think about, okay, well how do I get my active business moved over? But yeah. >>Yeah. And how do you guys see the whole cloud native scale moving with the hyper scales? Like aws? You've got a lot of multi-cloud conversation. We call it super cloud in our narrative, but there's now this new, we're gonna get some of common services being identified. We're seeing a, we're seeing a lot more people recognize and with Kubernetes that hey, you know what, you could get some common services maybe across clouds with SOS doing storage. We got Min iOS doing some storage. Yeah. Cloud flare, I mean starting to see a lot more non-hyper scale systems. >>Yeah, I mean I, and I think that's the pattern there and I think it, it's, especially for enterprise at the top end, right? You see a, a lot of companies are trying to de-risk by saying, Hey, I, I don't want to bet maybe on one cloud provider, I sort of need to hedge my bets a little bit. And Kubernetes is a great tool to go do that. You can imagine some of these other tools you mentioned is a great way to do that. Observability is another great way to do that. Or the cloud providers have their observability or monitoring tooling, but it's really optimized just for that cloud provider, just for those services there. So if you're really trying to run either your custom applications or a multi-cloud approach, you really can't use one cloud providers solution to go solve that problem. Do you >>Guys see yourselves with that unifying >>Layer? We, we, we are a little bit as that lay because it's agnostic to each of the cloud providers. And the other thing is we actually like to understand where our customers run and then try to run their observability stack on a different cloud provider. Cuz we use the cloud ourselves. We're not running our own data centers of course, but it's an interesting thing where everybody has a common dependency on the cloud provider. So when us e one ofs hate to call them out, but when us E one ofs goes down, imagine half the internet goes down, right? And that's the time that you actually need observability. Right? Seriously. And every other tooling there. So we try to find out where do you run and then we try to actually run you elsewhere. But yeah, >>I like that. And nobody wants to see the ugly bits anyway. Exactly. And we all know who when we're all using someone when everything >>Exactly. Exactly, exactly. >>People off the internet. So it's very, I, I really love that. Martin, Jeff, thank you so much for being here with us. Thank you. What's next? What, how do people find out, how do they get one of the jobs since three Xing your >>Employee growth? We're hiring a lot. I think the best thing is to go check out our website chronosphere.io. You'll find out a lot about our, our, our careers, our job openings, the culture we're trying to build here. Find out a lot about the product as well. If you do have an observability problem, like that's the best place to go to find out about that as well. Right. >>Fantastic. Well if you want to join a quarter billion, a quarter of a billion dollar rocket ship over here and certainly a unicorn, get in touch with Martin and Jeff. John, thank you so much for joining me for this very special edition and thank all of you for tuning in to the Cube live here from Motor City. My name's Savannah Peterson and we'll see you in a little bit. >>Robert Herbeck. People obviously know you from Shark Tanks, but the Herbeck group has been really laser focused on cyber security. So I actually helped to bring my.

>> Narrator: Live from San Diego, California. It's theCube! Covering KubeCon and CloudNativeCon, brought to you by Red Hat. A cloud native computing foundation. >> Welcome back. 12 thousand here in attendance for KubeCon CloudNativeCon 2019 in San Diego. I am Stu Miniman, my cohost for this afternoon is John troyer. And happy to welcome to the program, recently out of Stealth, two gentlemen from Chronosphere, Austin. To my right is Martin Mao who is the co-founder and CEO and his co-founder Rob Skillington, who's also the CTO, we've stated on theCUBE actually, you understand where this conference is, where co-founder and CTO is like you know, the most prominent title that we've seen to get on here, because that's the type of geeks we love on the program and in this community. So first of all, congratulations on the launch >> Thank you so much >> And thank you so much for joining us. >> No worries. >> All right, when I've got the founders on, I'm going to start with the whys. How was kind of the problem statement, where you were coming from, and what led to the creation of Chronosphere. >> For sure for sure. So with Chronosphere we found a actual gap in the monitoring market, and a very crowded monitoring market, we found a gap, and the gap exists when companies with very large complex technology stacks, or large enterprises, move on to Cloud Native Technology and Kubernetes. So with this migration, what we've found was there's actually a lot more monitoring data being produced, because there's a lot more pieces now, we're moving from monoliths microservices, we're moving from like physical machines to VMs, to containers and pods. And that generates a lot more things that you need to monitor and track. And not only a lot more things, but you generally monitoring the relationship between these things. So as the number of things increases, the number of relationships exponentially increases. So yeah, that's the sort of problem we're solving, it's like monitoring all of these things at large scale, and when we couldn't find anything, and I could even store all of theses things, so that's it sort of. >> All right, so what is the background of the team that made you into position to work on this problem? >> Yeah great question. I mean me and Martin go back quite a few years. I officiated his wedding, only very very recently actually. And I, yeah we basically work together at several different companies. You know, I think both of us are entrepreneurial at heart. I'll let Martin talk a little bit more about the last few years. >> Yeah, so like you know, a few years ago we started working at Uber. And at Uber, we went through this migrations to our native communities and through that migration that's when we sort of had to solve the problem ourselves. And we solved the problem at Uber, with an open-source project called M3. That's really where this whole thing started. And Chronosphere sort of you know, building on top of M3, and now providing a product on top of the open-source platform that we created. >> Can we talk a little bit about the business? I noticed that you know, there are many ways of approaching open-source, in 2019, you know open core and but also as a service. So can you talk a little bit about how you've approached your business model. >> Yeah for sure. So we're very much in the position or in the camp of as a service, right, because you know a lot of companies do do open core, and they're sort of going into the enterprise support model, we sort of didn't want to go down that route. And also with our open-source product, it's not really an end to end solution in itself, like you use an open-source M3, but you still need to plug it together with other things yourself. So what we really wanted to do was to give customers, and end to end solution, and that was built on top of the great technology, we built with M3, but really it solves the problem sort of end to end, and we do that best as a service. >> Rob maybe you can help explain M3 a little bit for us as to how that fits in the landscape, but what it works with and the like. >> Yeah of course. Yeah it's basically at it's heart a metrics platform, that is built on, at first the lower layer in 3DB, which is a distributive time series database. And then on top of that, we have basically an aggregation platform, that is actually aggregating a lot of the samples, and metrics that we're, collecting. So we can really do some transformations on the data, as it comes in, before it's stored in the database itself. And this let's us do a lot of like smart processing, of what signals actually matter, what signals don't matter, kind of like storing them in a way that can be accessed, much faster than like, other typical systems that don't really do any aggregation before it gets stored. And then, you know we have of course like a query engine that works with this distributed set of data, and so, you know, it's really a database that was designed from day one, to be a metric store. You know, it's not built on Cassandra, it doesn't use Rocks DB, at the lower layers, it literarily every part of it, was built for this purpose. >> Can you talk a little bit about dimensionality and cardinality? Because as I look at this observability monitoring space, I see a lot of current discussion about that and frankly a little bit of fighting, and I'm not always, I can kind of see it, why it's important, but what are some of the reasons and what do people do where you know by having it, and what is it actually, let's start with that. >> Yeah for sure. So you know, with this hot topic of like high cardinality and high dimensionality is, what I was talking about earlier, where as you move into cloud native world, you're now monitoring things at like a pod level. So it's like instead of tracking things on like a per host level, you're now tracking things on like a per pod level now, and that is at >> (interjects) You're tracking more things per pod. >> More things per pod and like every pod unit, these are ephemeral pods now, so they don't live for very long. So you end up having more pieces of data and they're kept around for shorter period of time. And now you need a system that can store all of these pieces of data, because you want to see them uniquely. So you want to monitor each individual pod to see exactly what is running at the finest levels. Right, so you actually need technology that can store a lot more data than you could before. >> And I you know, adding to that, there's a lot more people running with like mobile applications, they use you know that are running in markets all round the world, using different cell providers, and different backend services. You may deploy your backend services multiple times, a week or even a day, and if you want to tag you know, the meta data on and slice and dice by that metadata, with your business and with your applications and your system, that requires you know, adding yet another dimension on your data, which adds to that cardinality. Every time you add a dimension, you know that just multiplies the cardinality of your existing data set of monitoring data. >> And it quickly adds up a lot right, so. >> All right Martin, maybe, since you're just out of Stealth, give us some of the speeds and feeds you know, the product GA, is it globally available? Series A funding, who's behind that? >> Yeah so we just kind of still two weeks ago, we closed up Series A a few months ago actually. It was led by Great Luck, we raised 11 million dollars, and our partner at Great Luck is Gary, and we like him very much. And you know the state of the companies that we are currently in private beta right now. So with our hosted platform, we are onboarding to customers into a private offering right now. And early next year, we'll sort of open that up for more public beta. Yeah. >> And the way folks would use this. You'll be using Prometheus or Graphite or something, and you'd be, so you'd have tracing, you'd have logs, you'd have other things and you would be plugging all of them into, into your services. >> Yeah it's a great question. So you mentioned two of the technologies. So if you're Prometheus or Graphite like to try find metrics, both of those can be pushed into the M3 system for sure. We actually just announced a trace integration, this week a KubeCon actually, Rob David spoke about that integration earlier this week at KubeCon. We haven't moved into the logs yet because the way we look at the problem is not from like a sort of like providing a one-stop shop for all observability solutions, we actually look at it from a use case perspective. So the use case we're looking at is like, realtime monitoring and remediation. So tracing is a part of that stroy, it's a critical part of that story, and now to add additional context, when you get to load it based on your metrics, but, we haven't quite moved into logging yet. >> Yeah, and we don't really want to solve any of these problems without knowing it'll work at scale, you know like a fundamental reason we even built the open-source project in the first place, was we were dealing with cardinality in the tens of billions of unique time series, and so, we don't want to just kind of like roll into any, every single feature under the sun, we really want to solve it once correctly and be able to systematically roll that out to enterprises at scale. >> Without, I mean without talking too much about Uber and any Uber secrets, I mean it seems like the game has changed with that kind of a scale of, you could not have done, you can't run Uber if you're tracking all those cars like literarily without some sort of a tracing like high cardinality sort of a system right? Because you're literarily tracking cars all over the world people all over the world, routes all over the world. >> Exactly, well uniquely positioned, we had the requirements to solve it at such a scale, and that's why we had to build this technology to solve it for that unique situation, because you know technologies ahead of time, did not really have this use case to solve. So that's why we had to sort of, we couldn't find anything out in the market because to solve it at that scale, that's why we sort of had to build our own, to uniquely solve it for this use case. >> And yeah, I would add to that, that typically engineers you know, at larger organizations, tend to want to organize everything very nicely, and split it up, and really control how they're monitoring that data, but we've noticed actually, definitely over the last few years, more and more people are open to letting people just start collecting you know, random data, that is relevant to the systems that they're building as they're rolling it out, even as they're experimenting with it, and you know systems today that are built from scratch, to deal with, to be as efficient as possible, with very unstructured data is becoming wildly popular because that's how developers want to develop software. You know, they don't want to have to have to like slice and dice it neatly and package it up and pass it on to others to run. They want to basically slice and dice however they want to, and dynamically , and as they scale up. >> I've always enjoyed every sequel skimmer I've had two, or change oh, yeah. (laughter) >> All right, how have you found the show? How's the reception been? Give us a little bit of the vibe of the show and how it's been going for you. >> Yeah it's been fantastic for us actually. So we just came in at silk so like the name is still quite new, but yeah, we've had a bunch of folks set up with the whole day, we've been giving a demo on the product, so a lot of companies are getting excited about it. I think a we're solving at a scale and that really resonates with, you know, a lot of the people here at the show, we're still solving at a scope, we're solving at a scale that's also in a cost efficient way as well. So that's really been our, we sleep quite well so far. >> Yeah Rob, you gave some sessions. What kind of feedback are you getting from people? Is the problem statement that we talked about at the beginning you know resonating with people that you talk to. >> I mean, I was really, yeah pleased to hear that after my session today, that a lot of people came up to me and said you know, I've never really seen metrics been linked to tracers, the way that we're doing it, in fact that's the first time they'd ever seen a demo, that can do, what we're kind of trying to upstream, we're actually you know, up-streaming a lot of those changes in the open-source well, as well at the same time. And so, you know we've found especially in a lot of the companies today that are pushing everything forward with development wise and how they are running operations is that they using a lot of pages in open source, and then those pages are battle tested in open-source, generally it becomes abstracted, to the point where we're actually a very large amount of people, but then when they need to scale it up, that's when it becomes difficult. So, no I think that you know, a lot of people have been very positive with basically us being able to also push forward the feature on >> Back upstream into the M3 project. >> And also into Prometheus. So I, you know I'm an open metrics, contributor and that's essentially, an exposition format that's built on the Prometheus, exposition format. So it's kind of become a standard way of exchanging metrics, from one system to another. And that's kind of like, basically commoditized and democratize the exchange of metrics to make a lot more systems, interoperable with each another. Which we fundamentally believe in as well, of course we're developing in open-source, and we believe that this systems need to play nicely together. So we can build you know, have building blocks that large companies and organizations can all share and build better things on top of. >> All right, so looking to go to public beta early 2020s, what we said, when we come back in 2020, what kind of the, some of the key KPIs and metrics that you'll be looking at to be successfull in your first year out of Stealth. >> Yeah it's a great question. So you know, since some of the KPIs you guys were looking at doing is coming at the public beta, making it available to a large range of companies, because right now we're sort of onboarding companies sort of one or two at a time, so yeah it's seeing how many companies adopt the product and also, we're again adding more features over time, for that particular use case of like you know, monitoring your technology just like in your business in real time. So it'll be a lot more features coming down the pipeline, and a lot more customer adoption along with that. >> And I would also say you know, our hosted platform is really about offering like deep isolation, between our tenants as well, so basically when we you know, in the next few months to come, we want to make sure that it works basically like clockwork, and everyone can, we can roll out and scale that highly isolated platform for you know tens and hundreds of organizations, and thousands eventually. And so, and doing that at scale is hard. So I think yeah, we'll see how we're doing with that. >> Yeah for sure. >> All right. Rob, Martin congratulations on coming out of Stealth, look forward to hearing more and thank you so much for joining us. >> Glad, thank you so much. >> All right, for John Troyer I'm Stu Miniman, we'll be back getting towards the end of three days, want to walk over here KubeCon, CloudNativeCon thanks for watching. (upbeat music)

>> Welcome back to theCUBE's coverage of KubeCon + CloudNativeCon 21 live form Los Angeles. Lisa Martin, with Dave Nicholson. And we've got a CUBE alum back with us. Webb Brown is back. The co-founder and CEO of Kubecost. Welcome back! >> Thank you so much. It's great to be back. It's been right at two years, a lot's happening in our community and ecosystem as well as with our open source project and company. So awesome with that. >> Give the audience an overview in case they're not familiar with Kubecost. And then talk to us about this explosive growth that you've seen since we last saw you in person. >> Yeah, absolutely. So Kubecost provides cost management solutions purpose-built for teams throwing in Kubernetes and Cloud Native. Right? So everything we do is built on open source. All of our products can be installed in minutes. We give teams visibility into spend, then help them optimize it and govern it over time. So it's been a busy two years since we last talked, we have grown the team about, you know, 5 x, so like right around 20 people today. We now have thousands of mostly medium and large sized enterprises using the product. You know, that's north of a 10 x growth since we launched just before, you know, KubeCon San Diego, now managing billions of dollars of spin and, you know, I feel like, we're just getting started. So it's an incredibly exciting time for us as a company and also just great to be back in person with our friends in the community. >> This community is such a strong community. And it's great to see people back here. I agree. >> Absolutely, absolutely. >> So Kubecost, obviously you talk about cost optimization, but it's, you really, you're an insight engine in the sense that if you're looking at costs, you have to measure that against what you're getting for that cost. >> Absolutely. So what are some of the insights that your platform or that your tool set offers. >> Yeah, absolutely, so, you know, we think about our product is first and foremost, like visibility and monitoring and then insights and optimization and then governance. You know, if you talk to most teams today, they're still kind of getting that visibility, but once you do it quickly leads in how do we optimize? And then we're going to give you insights at every part of the stack, right? So like at the infrastructure layer, thinking about things like Spot and RIS and savings plans, et cetera. At the Kubernetes orchestration layer, thinking about things like auto scaling and, you know, setting requests and limits, et cetera, all the way up to like the application layer with all of that being purpose-built for, you know, Cloud Native Kubernetes. So the way we work as you deploy our product in your environment, anywhere you're running Kubernetes, 1.11 or above we'll run. And we're going to start dynamically generating these insights in minutes and they're real time. And again, they scaled to the largest Kubernetes clusters in the world. >> And you said, you've had a thousand or so customers in the medium to large enterprise. These are large organizations, probably brand names, I imagine we are familiar with that are leaning on Kubecost to help get that visibility that before they did not have the ability to get. >> Absolutely, absolutely. So definitely our users of our thousands of users, skews heavily towards, you know, medium and large side enterprise. Working with some amazing companies like Adobe, who, you know, just have such high scale and like complex and sophisticated infrastructure. So, you know, I think this is very natural in what we expect, which is like, as you start spending more resources, you know, missing visibility, having unoptimized infrastructure starts to be more costly. >> Absolutely. >> And we typically see as once that gets into like the multiple head count, right? And it starts to, you know, spend some, may make sense to spend some time optimizing and monitoring and, you know, putting the learning in place. So you can manage it more effectively as time goes on. >> Do you have any metrics or any X factor ranges of the costs that you've actually saved customers? >> Yeah. I mean, we've saved multiple customers in them, like many of millions of dollars at this point, >> So we're talking big. >> Really big. So yeah, we're now managing more than $2 billion of spin. So like some really big savings on a per customer base, but it's really common where we're saving, you know, north of 30%, sometimes up to 70% on your Kubernetes and related spin. And so we're giving you insights into your Kubernetes cluster and again, the full stack there, but also giving you visibility and insights into external things like external disk or cloud storage buckets or, you know, cloud sequel that, that sort of stuff, external cloud services. >> Taking those blinders off >> Exactly. And giving you that unified, you know, real time picture again, that accurately reflects everything that's going on in your system. >> So when these insights are produced or revealed, are the responses automated? or are they then manually applied? >> Yeah. Yeah. That's a great question. We support both and we support both in different ways By default, when you deploy Kubecost, and again it's, today it's Helm Install. It can be running in your cluster in, you know, minutes or less, it's deployed in read only mode. And by the way, you don't share any data externally, it's all in your local environment. So we started generating these insights, you know, right when you install in your environment. >> Let me ask you about, I'm sorry to interrupt, but when you say you're generating an insight, are you just giving an answer and guidance? or you're providing the reader background on what leads to that insight? >> Yeah. You know, is that a philosophical question of, do you need to provide the user rationale for the insight? >> Yeah, absolutely. And I think we're doing this today and we'll do more, but one example is, you know, if you just look at this notion of setting requests and limits for your applications in Kubernetes, you know, if you, in simple forms, if you set a request too high, you're potentially wasting money because the Kubernetes scheduler is presenting that resource for you. If you set it too low, you're at risk of being CPU throttled, right? So communicating that symbiotic relationship and the risk on either side really helps the team understand why do I need to strike this balance, right? It's not just cost it's performance and reliability as well. So absolutely given that background and again, out of the box we're read only, but we also have automation in our product with our cluster controller. So you can dynamically do things like right-size your infrastructure, or, you know, move workloads to Spot, et cetera. But we also have integrations with a bunch of tooling in this ecosystem. So like Prometheus native, you know, Alert Manager native, just launched an integration with Spinnaker and Armory where you can like dynamically at the time of deployment, you know, right size and have insights. So you can expect to see more from us there. But we very much think about automation is twofold. One, you know, building trust in Kubecost and our insights and adopting them over time. But then two is meeting you where you are with your existing tooling, whether it's your CICB pipeline, observability or, you know, existing kind of workflow automation system. >> Meeting customers where they are is, is critical these days. >> Absolutely. I think, especially in this market, right? where we have the potential to have so much interoperability and all these things working in harmony and also, you know, there's, there's a lot of booths back here, right? So we, you know, we have complex tech stacks and, you know, in certain cases we feel like when we bring you to our UI or API's or, you know, automation or COI's, we can do things more effective. But oftentimes when we bring that data to you, we can be more effective again, that's, you know, coming, bringing your data to Chronosphere or Prometheus or Grafana, you know, all of the tooling that you're already using on a daily, regular basis. >> Bringing that data into the tool is just another example of the value in data that the organizations can actually harness that value and unlock it. >> Webb: Yeah. >> There's so much potential there for them to be more competitive, for them to be able to develop products and services faster. >> Absolutely. Yeah, I think you're just seeing the coming of age with, you know, cost metrics into that equation. We now live in a world with Kubernetes as this amazing innovation platform where as an engineer, I can go spin up some pretty costly resources, really fast, and that's a great thing for innovation, right? But it also kind of pushes some of the accountability or awareness down to the individual >> Webb: IC who needs to be aware, you know, what, you know, things generally cost at a minimum in like a directional way, so they can make informed decisions again, when they think about this cost performance, reliability, trade-off. >> Lisa: Where are your customer conversations? Are your target users, DevOps folks? I was just wondering where finance might be in this whole game. >> Yeah, it's a great question. Given the fact that we are kind of open source first and started with open source, we, you know, 95% of the time when we start working with an infrastructure engineering team or dev ops team. They've already installed our product. They're already familiar with what we're doing, but then increasingly and increasingly fast, you know, finance is being brought into the equation and, you know, management is being brought into the equation. And I think it's a function of what we were talking about where, you know, 70% of teams grew their Kubernetes spend over the last year, you know, 20% of them more than doubled. So, you know, these are starting to be real, you know, expense items where finance is increasingly aware of what's going on. So yeah, they're coming into the picture, but it's simply thought that you starting with, and, and working with the infrastructure team, that's actually kind of putting some of these insights into action or hooking us into their pipelines or something. >> When you think of developers going out and grabbing resources, and you think of a, an insight tool that looks at controlling cost, that could seem like an inhibitor. But really if you're talking about how to efficiently use whatever resources you have to be able to have access to in terms of dollars, you could sell this to the developers on that basis. It's like, look, you have these 10 things that you want to be able to do. If you don't optimize using a tool like this, you're only going to be able to do 4 of them. >> Without a doubt. Yeah. And you know, us as our founding team, all engineers, you know, we were the ones getting those questions of, you know, how have we already spent, you know, our budget on just this project? We have these three others we want to do, right? Or why are costs going up as quickly as they are? You know, what are we spending on this application, instead of that kind of being a manual lift, like, let me go do a bunch of analysis or come back with answers. It's tools to where not only can management answer those questions themselves, but like engineering teams can make informed opportunity costs and optimizations decisions itself, whether it's tooling and automation doing it for them or them applying things, you know, directly. >> Lisa: So a lot of growth. You talked about the growth on employees, the growth in revenue, what lies ahead for Kubecost? What are some of the things that are coming on the horizon that you're really excited about? >> Yeah, we very much feel like we're just getting started you know, just like we feel this ecosystem and community is, right? Like there's been tons of progress all around, but like, wow, it's still early days. So, you know, we, we did raise, you know, five and a half million dollars from, you know, First Round who is an amazing group to work with at the end of last year. So by growing the engineering team were able to do a lot more. We got a bunch of really big things coming across all parts of our product. You can think about one thing we're really excited that's in limit availability right now is our first hosted solution. It's our first SaaS solution. And this is critically important to us in that we want to give teams the option to, if you want to own and control your data and never egress anything outside of your cluster, you can do that with our deploy product. You can do that with our open source. You can truly lock down namespace to egress and never send a byte out. Or if you'd like the convenience of us to manage it for you and be kind of stewards of your data, we're going to offer, you know, a great offering there too. So that's unlimited availability day. We're going to have a lot more announcements coming there, but we see those being at feature parity, you know, between like our enterprise offerings and our hosted solution and just, you know, a lot more coming with, you know, visibility, some more like GPU insights, you know, metrics coming quickly, a lot more with automation coming and then more integrations for governance. Again, kind of talked about Spinnaker and things like that. A lot more really interesting ones coming. >> So five and a half million raised in the last round of funding. Where are you going to be applying that? What are some of the growth engines that you want to tune with that money? >> Yeah, so, you know, first and foremost, it was really growing the engineering team, right? So we've, you know, like 4 x the engineering team in the last year, and just have an amazing group of engineers. We want to continue to do that. >> Webb: We're kind of super early on the like, you know, marketing and sales side. We're going to start thinking about that more and more, you know, our approach first off was like, we want to solve a really valuable problem and doing it in a way that is super compelling. And we think that when you do that, you know, good things happen. I think that's some of our Google background, which is like, you build a great search engine and like, you know, good things generally happen. So we're just super focused on, again, working with great users, you know, building great products that meet them where they are and solve problems that are really important to them. >> Lisa: Awesome. Well, congratulations on all the trajectory of success since we last saw you in person. >> Thank you. >> Great to have you back on the show, looking forward to, so folks can go to www.kubecost.com to learn more and see some of those announcements coming down the pike. >> Absolutely, yeah. >> Don't you make it two years before you come back. >> Webb: I would love to be back. I hope we're back bigger than ever, you know, next year, but it has been such a pleasure, you know, last time and this time, thank you so much for having me, you know, I love being part of the show and the community at large. >> It's a great community and we appreciate you sharing all your insights. >> Thank you so much. >> All right. For Dave Nicholson, I'm Lisa Martin coming to you live from Los Angeles. This is theCUBE's coverage of KubeCon and CloudNativeCon 21. We back with our next guest shortly. We'll see you there.

>>Hey, welcome back everyone to cube Cod's coverage and cloud native con the I'm John for your husband, David Nicholson cube analyst, cloud analyst. Co-host you got two great guests, KIPP alumni, Jerry Chen needs no introduction partner at Greylock ventures have been on the case many times, almost like an analyst chair. It's great to see you. I got guest analyst and Martin mal who's the CEO co-founder of Chronosphere just closed a whopping $200 million series C round businesses. Booming. Great to see you. Thanks for coming on. Thank you. Hey, first of all, congratulations on the business translations, who would have known that observability and distributed tracing would be a big deal. Jerry, you predicted that in 2013, >>I think we predicted jointly cloud was going to be a big deal with 2013, right? And I think the rise of cloud creates all these markets behind it, right. This, you know, I always say you got to ride a wave bigger than you. And, uh, and so this ride on cloud and scale is the macro wave and, you know, Marty and Robin cryosphere, they're just drafted behind that wave, bigger scale, high cardinality, more data, more apps. I mean, that's, that's where the fuck. >>Yeah. Martin, all kidding aside. You know, we joke about this because we've had conversations where the philosophy of you pick the trend is your friend that you know, is going to be happening. So you can kind of see the big waves coming, but you got to stay true to it. And one of the things that we talk about is what's the next Amazon impact gonna look like? And we were watching the rise of Amazon. You go, if this continues a new way to do things is going to be upon us. Okay, you've got dev ops now, cloud native, but observability became really a key part of that. It's like almost the, I call it the network management in the cloud. It's like in a new way, you guys have been very successful. There's a lot of solutions out there. What's different. >>Yeah. I'd say for Kearney sphere, there's really three big differences. The first thing is that we're a platform. So we're still an observability platform. And by that, I mean, we solved the problem end to end. If thinking about observability and monitoring, you want to know when something's wrong, you want to be able to see how bad it is. And then you want to able to figure out what the root cause is. Often. There are solutions that do a part of that, that that problem might solve a part of the problem really well for a platform that does the whole thing. And 10 that's that's really the first thing. Second thing is we're really built for not just the cloud, but cloud native environments. So a microservices architecture on container-based infrastructure. And that is something that, uh, we, we have saw coming maybe 20 17, 20 18, but luckily for us, we were already solving this problem at Uber. That's where myself, my co-founder were back in 20 14, 20 15. So we already had the sort of perfect technology to solve this problem ahead of where the, the trend was going in the industry and therefore a purpose-built solution for this type of environment, a lot more effective than a lot of the existing. >>It's interesting, Jerry, you know, the view investing companies that have their problem, that they have to solve themselves as the new thing, versus someone says, Hey, there's a market. Let's build a solution for something. I don't really know. Well, that's kind of what's going on here. Right? It's >>That's why we love founders. Like Martin Marna, rod that come out with these hyperscale comes Uber's like we say, they've seen the future. You know, like there were Uber, they looked at the existing solutions out there trying to scale Promethease or you know, data dogs and the vendors. And it didn't work. It fell over, was too expensive. And so Martin Rob saw solid future. Like, this is where the world's going. We're going to solve it. They built MP3. It became cryosphere. And um, so I don't take any credit for that. You know, I just look fine folks that can see the future. >>Yeah. But they were solving their problem. No one else had anything. There's no general purpose software that managed servers you could buy, you guys were cutting your teeth into solving the pain. You had Uber. When did you guys figure out like, oh, well this is pretty big. >>Uh, probably about 20 17, 20 18 with a rise in popularity of Kubernetes. That's when we knew, oh wait, the whole world is shifting to this. It's not, no one could really it to just goober and the big tech giants of the world. And that's when we really knew, okay. The whole, the whole whole world is shifting here. And again, it's, it's sheer blind luck that we already had the ideal solution for this particular environment. It wasn't planned it. Wasn't what we were planning for back then. But, um, yeah. Get everything. >>It makes a lot of difference. When you walk into a customer and say, we had this problem, I can empathize with you. Not just say we've got solved. Exactly. Jerry, how do they compete in the cloud? We always talk about how Amazon and Azure want to eat up anything that they see that might, you know, something on AWS. Um, this castle in the cloud opportunity here. Okay. >>In the cloud. I mean, you know, we talked last time about how to fight the big three, uh, Amazon Azure and, uh, and Google. And I think for sure they have basic offerings, right. You know, Google Stackdriver years ago, they've done basically for Pete's offerings, basic modern offerings. I think you have like basic, simple needs. It's a great way to get started, but customers don't want kind of a piecemeal solution all the time. They want a full product. Like Datadog shows a better user experience, but full product is going to, you know, the better mousetrap the world will beat a path to your door. So first you can build a better product versus these point solutions. Number two is at some scale and some level complexity, those guys can handle like the demanding users that current affairs handling right now, right? The door dash, the world. >>And finally don't want the Fox guarding the hen house. You know, you don't want to say like Amazon monitoring, you can't depend on Amazon service monitoring your Amazon apps or Google service monitor your Google apps, having something that is independent and multi-cloud, that can dual things, Marta said, you know, see a triage, fixed your issues is kind of what you want. And, um, that's where the market's skilling. So I do believe that cloud guys will have an offering the space, but in our castle and cloud research, we saw that, yeah, there's a plenty of startups being funded. There's plenty of opportunity. And that the scoreboard between Splunk Datadog and all these other companies, that there's a huge amount of market and value to be created in this piece. So, >>So with, at, at the time, when you, you know, uh, uh, necessity is the mother of invention, you're an Uber, you have a practical problem to solve and use you look around you and you see that you're not the only entity out there that has this problem. Where are we in that wave? So not everyone is at, cloud-scale not everyone has adopted completely Kubernetes and cloud native for everything. Are we just at the beginning of this wave? How far from the >>Beach are we, we think we're just at the beginning of this wave right now. Um, and if you think about most enterprises today, they're still using on, and they're not even in perhaps in the cloud at all right. Are you still using perhaps APM and solutions, uh, on premise? So, um, if you look at that wave, we're just at the beginning of it. But when, but when we talked to a lot of these companies and you ask them for their three year vision, Kubernetes is a huge piece of that because everyone wants to be multi-cloud everyone to be hybrid eventually. And that's going to be the enabler of that. So, uh, we're just in the beginning now, but it seems like an inevitable wave that is coming. >>So obviously people evaluated that exactly the way you're evaluating that. Right. Thus the funding, right. Because no one makes that kind of investment without thinking that there is a multiplier on that over time. So that's pretty, that's a pretty exciting place. >>Yeah. I think to your point, a lot of companies are running into that situation right now, and they're looking at existing solutions there for us. It was necessity because there wasn't anything out there now that there is a lot of companies are not using their sort of precious engineering resources to build their own there. They would prefer to buy a solution because this is something that we can offer to all the companies. And it's not necessarily a business differentiating technology for the businesses themselves >>Distributed tracing in that really platform. That's the news. Um, and you mentioned you've got this, a good bid. You do some good business. Is scale the big differentiator for you guys? Or is it the functionality? Because it sounds like with clients like door dash, and it looks a lot like Uber, they're doing a lot of stuff too, and I'm sure everyone needs the card. Other people doing the same kind of thing, that scale, massive amount of consumer data coming in on the edge. Yeah. Is that the differentiation or do you work for the old one, you know, main street enterprise, right. >>Um, that is a good part of the differentiation and for our product thus far before we had a distributor tracing for monitoring and metric data, that was the main differentiation is the sheer volume of data that gets produced so much higher, really excited about distributor tracing because that's actually not just a scale problem. It's, it's a space that everybody can see the potential distributor tracing yet. No one has really realized that potential. So our offering right now is fairly unique. It does things that no other vendors out there can do. And we're really excited about that because we think that that fundamentally solves the problem differently, not just at a larger scale, >>Because you're an expert, what is distributed tracing. >>Yeah. Uh, it's, it's, it's a great question. So really, if you look at this retracing, it captures the details of a particular request. So a particular customer interaction with your business and it captures how that request flows through your complex architecture, right? So you have every detail of that at every step of the way. And you can imagine this data is extremely rich and extremely useful to figure out what the underlying root causes of issues are. The problem with that is it's very bit boast. It's a lot of data gets produced. A ton of data gets produced, every interaction, every request. So one of the main issues are in this space is that people can't afford cost effectively to store all of this data. Right? So one of the main differentiators for our product is we made it cost efficient enough to store everything. And when you have all the data, you have far better analytics and you have >>Machine learning is better. Everything's better with data. That's right. Yeah. Great. What's the blind spot out. Different customers, as cybersecurity is always looking for corners and threats that some people say it's not what you want. It's what you don't see that kills you. That's, that's a tracing issue. That's a data problem. How do you see that evolving in your customer base clients, trying to get a handle of the visibility into the data? >>Yeah. Um, I think right now, again, it's, it's very early in this space of people are just getting started here and you're completely correct where, you know, you need that visibility. And again, this is why it's such a differentiator to have all the data. If you can imagine with only 10% of the data or 1% of data, how can you actually detect any of these particular issues? Right. So, uh, uh, data is key to solving that >>Feel great to have you guys on expert and congratulations on the funding, Jerry. Good to see you take a minute to give a plug for the company. What do you guys do? And actually close around the funding, told you a million dollars. Congratulations. What are you looking for for hiring? What are your milestones? What's on your plan plan. >>Yeah. Uh, so with the spanning, it's really to, to, uh, continue to grow the company, right? So we're sort of hiring, as I told you earlier, we are, uh, we grew our revenue this year by, by 10 X in the sense of the 10 months of this year, thus far. So our team hasn't really grown 10 X. So, so we, we need to keep up with that grid. So hiring across the board on engineering side, on the go to market side, and I just continue to >>Beat that. The headquarters, your virtual, if you don't mind, we've gone >>Completely distributed. Now we're mostly in the U S have a bunch of folks in Seattle and in New York, however, we going completely remote. So hiring anyone in the U S anywhere in Europe, uh, >>Oh, I got you here. What's your investment thesis. Now you got castles in the cloud, by the way, if you haven't seen the research from Greylock, Jerry and the team called castles in the cloud, you can Google it. What's your thesis now? What are you investing in? >>Yeah, it is. It is hard to always predict the next wave. I mean, my job is to find the right founders, but I'd say the three core areas are still the same one is this cloud disruption to Martin's point we're. So early days, the wave, I say, number two, uh, there's vertical apps, different SAS applications be finance, healthcare construction, all are changing. I think healthcare, especially the past couple of years through COVID, we've seen that's a market that needs to be digitized. And finally, FinTech, we talked about this before everything becomes a payments company, right? And that's why Stripe is such a huge juggernaut. You know, I don't think the world's all Stripe, but be it insurance payments, um, you know, stuff in crypto, whatever. I think fintechs still has a lot of, a lot of market to grow. >>It's making things easier. It's a good formula right now. If you can reduce complexity, it makes things easy in every market. You're going to seems to be the formula. >>And like the next great thing is making today's crappy thing better. Right? So the next, the next brace shows making this cube crappy thing. Yeah, >>We're getting better every day on our 11th season or year, I'm calling things seasons now, episodes and season for streaming, >>All the seasons drop a Netflix binge, watch them all the >>Cube plus and NFTs for our early videos. There'll be worth something because they're not that good, Jerry. How, of course you're great. Thank you. Thanks guys. Thanks for coming on it. Cubes coverage here in a physical event, 2021 cloud being the con CubeCon I'm John farrier and Dave Nicholson. Thanks for watching.

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hello everyone, welcome to this CUBE Conversation, I'm John Furrier, host of theCUBE I'm in the Palo Alto CUBE Studios here with the quarantine crew, doing the remote interviews during this time of COVID. Of course, we want to check in with all of our great esteemed guests and CUBE alumni. We're here with Jerry Chen, partner at Greylock. Jerry, great to see you, it's been a while. Hope you're sheltering in place, nice camera, nice set up you got there at home, thanks for coming on. >> Thanks, John. I set up all the cameras are just for you. Everybody needs their quarantine hobbies, and for me, I kind of dust off the audio visual playbook and set this up, just for theCUBE interviews. But it's good to see you. Glad you and the family are healthy and sane as well. >> Yeah, and same to you. Let's just jump into it, obviously, COVID-19 has caused the virtualization trend, virtual everything. You're no stranger to virtualization, and VMware back in the day really changed the game on server virtualization, but the whole world's becoming virtual. And it's very interesting because now people are feeling, but we in the industry have been talking about inside the ropes for a long time, which is, the future is there, it's going to be about interactions online, software, cloud scale, these things just got accelerated, and the disruption, the change of behavior, Zoom fatigue, Webexing, all this stuff that's happening, people are kind of like, "Wow! This is the future." This is a real impact, and it's mainstream, everyone's feeling about business, to personal, your thoughts? >> Yeah, I think Satya Nadella at Microsoft had this quote recently that they've seen two decade's worth of digital acceleration and transformation in just two months, and I think what we've seen the past four months, John is all the kind of first order effects of virtualization events, not just infrastructure, but like virtualization meetings and people, telemedicine, telehealth, online education, delivery of food, all those trends are just accelerated. We're buying stuff on eCommerce, and Amazon, and Instacart before hand, that's just accelerated. We're moving towards virtualized events, online education, online healthcare, that's just accelerated. So I think we're seeing the first order effects of changing not only how we work, how we communicate, but how we shop, interact, and socialize, it compress two decades within two, three months. And so I think that's changing both how you and I interact and how we build relationships, also how companies interact with their customers, and how companies interact with employees. and it's been exciting time, because one, when there's disruption, there's opportunity, but two is giving guys like you and me a chance to kind of dust off or try new skills, and you and I are both figuring out how to exist and thrive in this role where we're now interacting in this virtualized world. >> And it's still the same game personal relationships. Content is now data. This is stuff that we've been preaching on theCUBE. You've been on many times talking about, I going to get your thoughts as a venture capitalist, whether you're making bets on the future for investments, you have a 10 year horizon, and roughly speaking average on VC deals, enterprises and customers who are building a cloud and data centers, they got to make new bets or double down on stuff they've been doing, or cancel stuff that they had going on, and refactoring. So I want to to get your thoughts on one, first on the VC side, how have you guys refactored your thinking, your meetings, and your bets? >> Yeah, so I would say, three areas, one is how we operate as a VC firm what's changed? Number two, I'll talk about what we're investing in what's good or bad, and thirdly is like, what I think changes for our portfolio companies and how startups think. So first and foremost obviously, we've gone all virtual too, with shelter-in-place, our entire team is now working remotely, working from home, but we're still open for business and we're looking to find new investments, we are investing aggressively right now, and we're just doing things over Zoom. And so we're either A, doing video calls as a partnership, or doing video calls with startups that we're meeting and founders, but I'll be honest, one thing I've done John, is I've turned off the screen more or less, I've done more phone calls because I find that a video call is great for the first or second meeting, but with a founder or executive you have relationship with, it's just really nice to actually, go on a virtual walk where me and the founder of both put AirPods or take the phone to walk outside and kind of have a conversation, that's a little of a higher bandwidth. So, I think how we're operating has changed a little bit, but to your point, is the same business, connecting with a person one-on-one, reading the market, reading the founder, and making a bet. So that hasn't changed. I think on the stuff we're investing in, like you said, all the trends around cloud and APIs and SaaS, that's accelerated. So all the trends around the new workplace, SaaS companies, collaboration, going cloud that's accelerated faster, so some of our companies like Cato Networks that does software defined, wide area networks plus cloud security that just accelerated there in this market called secure access serves edge. We've seen kind of a nice tailwind from that, more and more data is going to cloud so companies like Rockset, that's a database company that you had on theCUBE, they're going to see a benefit from that because more and more data is now in the cloud. Then finally for the founders we work with, the way to go to market, the way to sell like no one's flying around selling one-on-one anymore, you're not meeting a CSO, or the CIO over steak dinner, or you're not going to a conference anymore. So a lot of our companies are figuring out how to do more online sales, bottoms ups adoption, that could be an API, that could be open source, we're trying to find a couple more of our line of business entry to the company and sell that way, versus go to a conference or for one-on-one meeting. So it's interesting, everything's moved faster, but then this slight curve ball on how you connect with your customer has changed. And so what's the Darwin line, it's not the strongest that survives, but the most adaptable. So we're seeing the companies that founders that are most adaptable right now, they're going to thrive. >> It's interesting, we've always talked about from a tech standpoint with DevOps and cloud-native, integration or horizontally scalable has been that ethos of value creation, you've talked about moats in the past, but now it's more real life, is becoming immersed into software, and so I want to get your thoughts on this, and we have a phrase here in theCUBE team is that, every company will become a media company, that's something that we believe in, and you starting to see that people are doing more Zooms, doing more digital events, you mentioned some of the other things. Can you see any other examples where a company has to become blank? Because media is just one element of the new realities of life, right? You got to broadcast, and you got to share your stories and formats, that's media, is there other areas we're seeing, that things that weren't on the radar before with COVID, where companies have to become something like, every company will be blank? Fill in the blank. >> I would say, it's trite to say one, one, was every company is a data company, people have been saying that for a while, that's more true than ever. Number two, I'll be honest, every company now is a healthcare company, right? Because be it in health insurance for employees, the current pandemic is making the reality of both physical health, and emotional health, and mental health key for employees. And so if that was a top cost factor for hiring employees, this could be even more important going forward that every company is a health care company. And thirdly, like you said, every company becomes media company, I would say every company is also either one or two things, they're a Fintech company, because every company is now going online with their content. They wanting to create a one-to-one commercial relationship with a customer, right? That could be ads, could be transaction, could be selling something, so you're now doing business directly with your customer, so every company is a Fintech company, and I would say every company's now also, like you said, content company, right? It's the media creating, but also the data you're taking, the value you add on top of the data you're creating, and then how you share that back to your customer. So you as an enterprise company or a consumer company, you collect data from users, you're to use that data to improve your product, and this could be a SaaS offering, this could be an application, but then take that data through real time analytics, then make your product better and so because of that, if you're a data company, real time data, like our database company mentioned earlier, Rockset becomes more important. If you're a Fintech company, so all things around payments or commercial banking and relationship with your customer make sense. And if a you're a healthcare company because all your employees are now caring about healthcare, just thinking about how to make communication of healthcare with employees a lot more efficient, and a part of the reason why to work for theCUBE and work for a startup is important, so I think those three things are top of mind for all employees and all employers. I think things could change the next six or nine months, but right now I see those three being front and center. >> It's interesting. I wonder if you can add real estate company to that because if you look at the work from home, it's dynamic. >> Yeah >> I had a friend who was a fellow dad with my son's lacrosse team, he lives in Los Gatos, he's been involved in Google, Tesla, building up their facilities, and he had an interesting guest post on SiliconANGLE, and he was saying, it's not just give them some extra pay for their internet access, companies got to rethink the facilities question, right? Because do you pay rent for your employees? Do you provide the VPN, beyond VPN security, for instance? So again, you start to see these new opportunities or challenges, open up new thinking, this is going to be a wave of opportunity. >> Well, that virtualization between work and home has now been blurred like you said earlier, John and so if you're a technology company that enables remote access or distribute access, like Cato Networks when the portfolio comes and Greylock around our road office, home office, that is now how to right? So I had this conversation with Jason of Austin, askSpoke, one of our companies, there's like a mass of hierarchy for working out, and at the base of the mass of hierarchy is like good internet access, right? That's the how to, you need security, right? Because if you don't have secure access, you can't work, and then you have information management, knowledge management, how to communicate, right? And then collaboration, so, you have now this new hierarchy of what is required you to work in this new world, but also the tools and the technologies, be it secured access service edge like CATO or IT Helpdesk for all employees like askSpoke, both of those things become dial tone for any remote work. Just like videoconferencing, we couldn't do this in the same way, 10, 15 years ago, that's become kind of a must have, and so I think it'd be fascinating how we went from the office world where I gave you a laptop, or a computer, or a desk to this home office world, where maybe you now I have to pay for my fancy camera setup and my VPN. >> Well certainly you're getting good ROI on your setup and sure Greylock will take care of that plenty of dough big, billions of dollars under management. And by the way, must have hire things in our houses, ping and internet access, so we fight for that ping time, I got 12 I'm like what's going on? Who's gaming? We have to get the kids off of Twitch, and whatnot. but in all seriousness, this is what the reality is. So now for the average person out there, there's a lot of discussion around mental health, you mentioned taking it off the video conferencing and going for a walk, or just talking on the phone, this speaks to the humanization aspect of what's going on, mental health, social interaction, we're social creatures, collaboration has to be re-imagined. What's your view on all this? >> I think absolutely, look, humans are social creatures by nature, and I think part of the reason why I had this conversation with my founders early during COVID-19, that it's both a healthcare crisis. It's an economic crisis with all the million and millions of people unemployed, but it's also an emotional crisis because one, we're not connected to family, friends, and loved ones, and we're sheltering home with either ourselves or just a handful of people. And so we're trying to figure out ways to like, recreate social connections, and that's a phone call, it's a video call, it's Zoom dinners, it's Zoom dinners, the Zoom parties, is key. I think, going on socially just in walks is another thing to kind of like, play and experience things together. But my two cents is if you're a startup, right now, it can help connect people work-wise or socially, that's just going to be super critical for the new experience. And I think people are discovering new ways to use technology, so Zoom was never meant to be used the way it is today, I think that's amazing. I think how people think about voice video, and email, and chat are changing as well. So I'll finding new ways to like, play games online with my nieces, or communicate with them. And I think as an employer in these companies, like HR software, and how you like manage, and coach, and lead your employees is going to change as well. And so, you have this world where we're all in one building, and think about how you as a CEO, or as a leader now can actually coach, develop, and enable your employees across the world. >> I want to get your thoughts on cloud, we've had many conversations around cloud computing as to rise of AWS, I remember one it was a big Twitter conversation, I think about last year where what enabled Amazon and I think one of the things that came out of it was virtualization enabled them to have all these different servers. What do you see coming out of this virtualization of our lives with the COVID-19, as people start to figure out beyond the triage of stabilization, and as they get foundationally set up in COVID, coming out of it, companies and people have to have a growth strategy, whether it's life or business, people want to come out of this on the upside, whether it's emotional or with their business, what do you see being enabled? What needs to be in place? What kind of scale? What kind of environment? Because this is where I think the entrepreneurs are really going to sharpen their energy on their creativities looking at the expectations and experience needed coming out of this, it may look completely different than what we were talking about a year ago. What's your thoughts? >> Well, I think individually, people can use this time to prove their skills in different ways. So I think as an employee, as CEO, as a founder, you take the time to like invest in new skills, and that could be, "Hey, how do our community collaborate and manage my team remotely?" So I think CEOs and founders that can understand how to motivate, educate, train their employees in this new world, well, those are skills going forward. So communication has always been a great skill John, for any leader, any founder, it's 10X more important in this new virtualized work role, communication, motivation, and leading people over remote work is going to be a new skill that people have. Managing remote teams, managing fully distributed teams or half distributed, half headquarters, so understanding how to organize and lead your team in this kind of half in the office half out of the office role, that's going to be a challenge as well. So any tools, technology and tips there, but I think in terms of the founders that can now hire employees, find customers, sell customers, and manage a distributed team, those three things in this new world, even post COVID-19, we're not going back to the way we were, so the ability to actually use skills around email, creating content, Slack, Zoom, video chat, online conferences, what was that? "Video Killed the Radio Star", the first MTV Video. So, COVID-19, and Zoom, and video collaboration, what's that do to the old skills or the old founders? And what do they enable? So just like TV replaced radio as a medium, and now this virtualized world is going to replace kind of the medium we had beforehand, so, there'll be new generation of founders and investors coming out of this generation that would be for the next 10, 15 years, and I'm excited to be part of that. >> Yeah, and it's super big opportunity, because you have these kind of medium changes, new protocols get developed, new responsibilities and roles emerge, value creation capture, equations change, right? So you're looking at things like online events, for instance, they don't happen anymore, and even when they do come back they'll probably be hybrid anyway. So you got virtual, hybrid, public it sounds like a cloud play to me, public events, hybrid events, and private events, I guess. >> Yeah, virtual private events, but the same thing holds, just like cloud internet increased the reach, right? So all of a sudden, you can reach a bigger audience than just radio, TV, or the newspaper. Now you have these virtualized events like say private events, public events, hybrid events, you as a company or a media property, like theCUBE can now reach a larger audience, right? It's global, you don't have to be there in person, you're going to have the remote audience as a first class citizen, now more than ever, it's just like the internet replacing newspaper and print, people really care about print and newspaper, but really the reach online is always a magnitude larger than print, so all of a sudden you thought more about the print, so the online audience more than print audience. So now going forward, you're going to think about the virtual audience that's remote versus the physical audience. And so you're going to have to create experiences that are their world class or both properties. So just like the cloud, you think about the big three cloud providers, private cloud, as a technology company, you think about all three venues, all three infrastructures as a first class citizen. It's not going to be all one cloud, it's not all going to be one note, if you will. So it forces everyone to think, not just kind of one path, but multiple paths, so like classic problems a lot of founders think, okay, I'm going to do an enterprise private cloud strategy only or I'm going to do a cloud only SaaS strategy. Now founders of this do both the same time, I got to address the private cloud on premise business at the same time as the cloud business, and not just one cloud, three or four clouds around the world. So it forces founders to be able to do more things at one time and the ability for a company to attack multiple venues or multiple territories at the same time, they'll be successful. And the days where I can just do one cloud or one venue, or one audience, those are gone, and so, folks like yourself, John, and what you've built here at theCUBE with everyone else, they can reach multiple audiences at the same time, that's going to be very powerful. >> And we're going to be marketing and doing a lot more online events, like you said, it's going to be easier to tap into our 7000 plus alumni to get people together to create great content. And again, content value to remote audience is interesting. So that shifts into the conversation that everyone talks about the remote worker. Well, what about the remote customer, the remote prospects? So this is going to change how companies have to be change of behaviors. And it's going to be driven by developers, because it's not like one app can solve it, 'cause you got to integrate, you got to have some integration points. So this is the question, are we moving away from that monolithic SaaS app? Or is it going to be some SaaS apps that need to integrate with others? Will there be an abstraction layer of innovation around? Because at the end of the day, these new workloads and new apps going to be built. If you're going to run an event, if I'm a SAP or a big company, I'm not going to rely or may not want to rely on a vendor. In fact, the CEO of SAP said, 'cause their site crashed for their event, "I'm not going to rely on a third party to run my business event." 'Cause their business model is the event, not just a supplier selection for a SaaS app. So interesting kind of new surge of online activity might tip the scales for the supplier side. >> I think you're right John, I think because now the, just like the IT technology is now your business, you're going to basically do one or two things, one, vet the IT technology provider that much higher or harder. But number two to your point, I think the way you sell and you reach companies is going to be through developers and yes, you're going to have these large monolithic SaaS apps before, but almost every SaaS app now has APIs for integration, and so to your point, is that integration and the ability to have multiple companies work together, and share data, and collaborate, that's going to be more important. And so really at Greylock and myself, I've been investing in developer-led technologies and developer-led adoption, or API, or open source-led adoption, for seven plus years now. And the truth of matter is, that's going to be even more powerful going forward. Nassim Taleb would say that's anti-fragile, right? So having one giant app is fragile, but having a bunch of small apps, or a bunch of APIs, or a bunch of developers using your open source technology, or using your API technology to build an application, that's anti-fragile, because at the end of the day, that's going to be more reliable for your customer than a single point of failure, which can be one giant application. So all the big apps like Salesforce, have now other platforms, right? They have APIs, they have extensibility, they understand that there's a long fat tail of solutions needed to build. And all the new startups are doing open source, or API-led adoption 'cause they understand that the fastest route to create value for the customer, is also the most robust technology stack that a customer can build upon. I think that's super insightful, in fact, that is, I think so compelling, because if you think about it, that's the formula for great investments from a startup standpoint. But now, because of COVID, you said, everything's been pulled forward and accelerated at the same time, there's a collision, not all the enterprises are that strong, they're not that developer-led. So I think, to the point about acceleration, now, the enterprises, and we've seen pockets of this with cybersecurity where they have their own, in-house teams doing a variety of different development. The customers have to be developer-led, because that's where the value is, so they have to have a supplier with the right stack and integration frameworks. Now, the customers who haven't really been developer-led, have to be developer-led, what's your take on that? >> Absolutely true. 20 years ago, the CIO of a company that used to be the monopoly supplier technology for the company, they decided what hardware to use, what servers, what stores to use, what applications to buy. And then all of a sudden, like Amazon came around and said, "Well, look, here's a set of APIs, go build what you want." And so the competition for kind of like the centralized decision making became Amazon. And guess what? CIOs reacted, they got better, they got smarter, and those that embrace kind of like an API developer-led adoption, became the CIOs you wanted to have in the company. So I think, CIOs in this cloud mobile era have adopted that philosophy that, look, my job now as the CIO is to enable my developers, my employees, which really the assets of the company is the people, to have the right tools. So you're asked a bunch of cloud APIs, like Rockset or whatever for data, or here's a bunch of resources, or open source technologies for you to pull. So like I invested in a company recently called Chronosphere, it's an open source technology around metrics and monitoring. So, "Hey, use this open source time series database for monitoring your cloud and build upon that," and they're not going to say, "We're going to pick one large vendor that's monolithic," we're going to say, "Here's an open source tech company or a cloud API, go build upon that." And the companies that are embracing that philosophy of API-led or developer-led, John, they're going to be far ahead the better CIOs, the better companies, because the rate of digital adoption has just gone exponential, so we were on this super fast path already, and with quarantine in COVID, we've accelerated all that digital transformation, so every brick-and-mortar retailer now has to be eCommerce retailer. So they're making a slow digital transformation to go from brick-and-mortar stores to online stores. Now like brick-and-mortar retail is pretty much not happening, and probably won't come back to the same levels for a while, they need to accelerate their move towards digital transformation, right? >> And IT certainly exposes the people who haven't really made those investments, because literally action and the mandate, now take action, make those changes, totally want to dig into this developer-led vision, because I think that's very real. And the new decision is going to be made on what to do. I'm happy to see the DevOps thinking, the agile, speed become the table stakes. So with that, this week, Google is having their nine-week digital event of 200 plus sessions, essentially, an asynchronous event, it's going to be sprinkled out, they've kind of pretty much released the videos, most of them today. Over the next eight, nine weeks, you're going to see a lot of videos. Google, one of the big three got AWS, Azure, Google, what's your assessment of the horses on the track relative to the cloud? >> I've been talking about this for seven, eight, nine years, I first met it, like in the first or second Amazon reinvent and what was the forecast? And we said, well, it's not a winner take all, but right now, it's a winner take most. Amazon's clearly the market share leader, Azure coming up quickly behind the enterprise, Google's a third but they're doing some smart things around technology. Google announced a bunch of things today, which I think are very smart. So for example, they announced BigQuery Omni, which is BigQuery that's in query, their kind of a data warehouse, also query data and private cloud Azure or Amazon. And so strategically, if you're the number three player, you're going to push a multi-cloud agenda with BigQuery Omni, or Google Anthos, which is kind of a multi-cloud platform. And for Google, I think is the right strategy. I also think it's the right strategy for most customers to be multi-cloud, because you can't be dependent upon, a single point of failure in your applications. You can't be dependent on a single cloud as well. So I think multi-cloud is probably the direction we're headed as cloud matures. And I think Google's making a bunch of the right choices around embracing multi-cloud, and today they made that choice with BigQuery Omni, and so I think they're playing catch up but they're playing that game. I think Amazon's clue is still in the lead and still it blows my mind, and it's continuing to impress me what they've done over the past 10 years in terms of improving the cloud offering and the cloud services up and down the stack, and I think the past five, six years, what Azure has done, has been super impressive in terms of, Microsoft embracing, open source embracing, cloud as an ethos against their legacy business of operating systems and servers on premise, they've done a great job of embracing the next generation. But I do think, looking around the corner this new developer-led mindset is going to matter, right? So the cloud tomorrow will be APIs, like Stripe for payments, Twilio for communication. So I see the next evolution not just being VMs and containers, but also a bunch of cloud services around data, security, and privacy. And the cloud vendors can build this next generation of database APIs, or privacy APIs, security APIs, that they're going to be in the catbird seat for the next 10 years of applications are going to be built. >> And it'll be interesting to your developer-led position, our conversation around that, if the developer is going to be leading, is it going to be an abstraction layer across multiple clouds? Or do I have to have my Google developers, and my Amazon developers, and my Azure developers? How do you see that playing out? Because I do believe developer-led is the way, the question is, how do you avoid forking resources, right? So you might want to have an (mumbles) I get that, but if I'm going to go double down on say, a cloud, I'm going to go deep, I'm going to hire developers. >> It's interesting, history suggests you have multiple teams remember, we used to have a Unix team or a Sun team inside companies, right? You had a Windows team, you had a kind of a Solaris and Linux team, and there's a Microsoft team, and a non-Microsoft team, in most companies and they didn't really work well together and they had kind of two groups in most companies. I think that was an okay way to get started, but ultimately, to your point, that was not cost effective at all, it was defeating, you see now you had to like have to rethink it, what was my data backup strategy? Okay, I have a Windows backup strategy, and a Unix Solaris backup strategy. So I think we're not going to make the same mistake again, right? I think what will happen, we'll going to have multiple clouds, Amazon, Google, Azure, and then on premise private cloud, so call it, three, four, or five clouds. And then you're going to have a set of tools that can abstract away, not 100% of the clouds, but I think the best developer tools, the best APIs will be multi-cloud. So I can get 80% or 90% of what I want to be done through this developer-led layer of APIs, be it databases or analytics. And then, 10 to 20% of the code, you can write will be able to take care of what's unique to Amazon, what's unique to Azure, what's unique to Google or what's unique to your own private cloud. But I think we're seeing a layer of technology and that's true to all the startups. With back and true to all the startups I see that lets you get most of the way done with a single platform, seamlessly AI technologies, and that's what customers want, right? They don't want to create modal fiefdoms, they want-- >> They want choice. The want choice, but the reality is they don't always get it. I want to go through a throwback to 2010 when Paul Maritz, head of the VMware our first CUBE gig, he said, there's a hardened top. Okay, the hardened top was, you don't worry about what's underneath the top, we're just going to focus on top of the stack that was classic kind of, the stack would develop and you'd had standardization. You mentioned you had Windows teams and Unix teams, but also you could argue that, back then you had Cisco and Wellfleet vendors, but you didn't have two teams of routers, you had one standard that ran the remote interoperability, and OSPF routing, or whatever you had going on, so you had some standardization, how do you view that? Because you want some standardization to have the interoperability, the SLAs and the security, at the same time you want to have flexibility, kind of above what may be called a hardened top, is there a hardened top in multi-cloud? >> I'd say hard top doesn't exist in same way. I think back in the day, you had proprietary technologies, operating systems and firmware, right? So windows was closed, a lot of the network operating systems were closed source. Now you can't get away with that. So you have open source technologies today and public APIs. And so the pressure of both one, competition, two, public APIs that people can read, copy, adjust, three, open source, and it's just customer demand not to be locked into a hard top anymore, that's largely going to go away. So I think most of the major vendors success will try to kind of more or less lock you in and keep you stuck on their platform, their technology, and that's fine, right? Every successful company should be able to do that. But I think the ability to lock you in through proprietary software or operating systems, that's not going to happen anymore. I see through cloud and open source, what we've seen is kind of interoperability, and flexibility is the default, if you can't meet those needs, customers will go other ways. There'll be proprietary technologies, proprietary extensions along the way, but 60, 70% of what you want is going to be compatible with most technologies and most clouds. If you're not going to offer choice and freedom to our customers, they'll go elsewhere. If you don't offer a flexible solution, John, someone else will, and the customers will choose a more flexible solution. >> I would agree with you. Outside of latency, which is laws of physics, value is the lock in, if you're creating value, that's really what the customers want, they get to capture that value. Well, Jerry, great to have you on. I love the new setup. We're going to have to make this more of it. We can bring you in on the podcast when we get Zooms over the weekend, maybe put a panel together. Let's get Carl Eschenbach some VMware alarms to come on, give the perspective, what's going on. And I thank you for taking the time and great to see that you're healthy and doing well. Thanks. >> Me too. Thanks, john. Anytime, I love to be on theCUBE, so I look forward to my next trip. >> All right, Jerry Chen, great CUBE alumni, our first interview over nine years ago, he brought that up. That was at the second reinvent, boy has the world changed, and it's only going to accelerate even faster. Everything's changing new bets are being made, decisions have to be evolving quickly and faster. If you're not fast, you will be in the pile of dead companies and not making it. So, Jerry Chen breaking it down as venture capitalist for Greylock. I'm John Furrier with theCUBE. Thanks for watching. (soft music)

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS reInvent 2019. Brought to you by Amazon Web Services and Intel along with it's Ecosystem partners. >> Well, welcome back, everyone theCUBE's live coverage in Las Vegas for AWS reInvent. It's theCUBE's 10th year of operations, it's our seventh AWS reInvent and every year, it gets better and better and every year, we've had theCUBE at reInvent, Jerry Chen has been on as a guest. He's a VIP, Jerry Chen, now a general partner at Greylock Tier One, one of the leading global Venture capitals at Silicon Valley. Jerry, you've been on the journey with us the whole time. >> I guess I'm your good luck charm. >> (laughs) Well, keep it going. Keep on changing the game. So, thanks for coming on. >> Jerry: Thanks for having me. >> So, now that you're a seasoned partner now at Greylock. You got a lot of investments under your belt. How's it going? >> It's great, I mean look, every single year, I look around the landscape thinking, "What else could be coming? "What if we surprise this year?" What's the new trends? What both macro-trends, also company trends, like, who's going to buy who, who's going to go public? Every year, it just gets busier and busier and bigger and bigger. >> All these new categories are emerging with this new architecture. I call it Cloud 2.0, maybe next gen Cloud, whatever you want to call it, it's clear visibility now into the fact that DevOps is working, Cloud operations, large scale operations with Cloud is certainly a great value proposition. You're seeing now multiple databases, pick the tool, I think Jassy got that right in his keynote, I believe that, but now the data equation comes over the top. So, you got DevOps infrastructure as code, you got data now looking like it's going to go down that same path of data as code where developers don't have to deal with all the different nuances of how data's stored, how it's handled, where is it, warm or cold or at glacier. So, developers still don't have that yet today. Seems to be an area of Amazon. What's your take on all this? >> I think you saw, so what drove DevOps? Speed, right? It's basically how developers shows you operations, merging of two groups. So, we're seeing the same trend DataOps, right? How data engineers and data scientists can now have the same speeds developers had for the past 10 years, DataOps. So, A, what does that mean? Give me the menu of what I want like, Goldilocks, too big, too small, just right. Too hot, too cold, just right. Like, give me the storage tier, the data tier, the size I want, the temperature I want and the speed I want. So, you're seeing DataOps give the same kind of Goldilocks treatment as developers. >> And on terms of like Cloud evolution again, you've seen the movie from the beginning at VM where now through Amazon, seventh year. What jumps out at you, what do you look at as squinting through the trend lines and the fashion of the features, it still seems to be the same old game, compute memory storage and software. >> Well I mean, compute memory storage, there's an atomic building blocks of a compute, right? So, regardless of services these high level frameworks, deep down, you still have compute networking and storage. So, that's the building blocks but I think we're seeing 10th year of reInvent this kind of, it's not one size fits all but this really big fat long tail, small instances, micro-instances, server lists, big instances for like jumbo VMs, bare metal, right? So, you're seeing not one architecture but folks can kind of pick and choose buy compute by the drip, the drop or buy compute by the whole VM or whole server full. >> And a lot of people are like, the builders love that. Amazon owns the builder market. I mean, if anyone who's doing a startup, they pretty much start on Amazon. It's the most robust, you pick your tools, you build, but Steve Malaney was just on before us says, "Enterprise don't want power tools, "they're going to cut their hand off." (laughs) Right so, Microsoft's been winning with this approach of consumable Cloud and it's a nice card to play because they're not yet there with capabilities with Amazon, so it's a good call, they got an Enterprise sales force. Microsoft playing a different game than AWS because they have to. >> Sure I mean, what's football now, you have a running game, you need a passing game, right? So, if you can't beat them with the running game, you go with a passing game and so, Amazon has kind of like the fundamental building blocks or power tools for the builders. There's a large segment of population out there that don't want that level of building blocks but they want us a little bit more prescriptive. Microsoft's been around Enterprise for many many years, they understand prescriptive tools and architectures. So, you're going to become a little bit more prefab, if you will. Here's how you can actually construct the right application, ML apps, AI apps, et cetera. Let me give you the building blocks at a higher level abstraction. >> So, I want to get your take on value creations. >> Jerry: Sure. >> So, if it's still early (mumbles), it's took a lot more growth, you start to see Jassy even admit that in his keynotes that he said quote, "There are two types "of developers and customers. "People want the building blocks "or people who want solutions." Or prefab or some sort of more consumable. >> More prescriptive, yeah. >> So, I think Amazon's going to start going that way but that being said, there's still opportunities for startups. You're an investor, you invest in startups. Where do you see opportunities? If you're looking at the startup landscape, what is the playbook? How should you advise startups? Because ya know, have the best team or whatever but you look at Amazon, it's like, okay, they got large scale. >> Jerry: Yeah. >> I'm going to be a little nervous. Are they going to eat my lunch? Do I take advantage of them? Do I draft off them? There are wide spaces as vertical market's exploding that are available. What's your view on how startups should attack the wealth creation opportunity value creation? >> There, I mean, Amazon's creating a new market, right? So, you look at their list of many services. There's just like 175 services out there, which is basically too many for any one company to win every single service. So, but you look at that menu of services, each one of those services themselves can be a startup or a collection of services can be a startup. So, I look at that as a roadmap for opportunity of companies can actually go in and create value around AI, around data, around security, around observability because Amazon's not going to naturally win all of those markets. What they do have is distribution, right? They have a lot of developer mind share. So, if you're a startup, you play one or three themes. So like, one is how do I pick one area and go deep for IP, right? Like, cheaper, better, faster, own some IP and though, they're going to execute better and that's doable over and over again in different markets. Number two is, we talked about this before, there's not going to be a one Cloud wins all, Amazon's clearly in the lead, they have won most of the Cloud, so far, but it'll be a multi-Cloud world, it'll be On Premise world. So, how do I play a multi-Cloud world, is another angle, so, go deep in IP, go multi-Cloud. Number three is this end to end solution, kind of prescriptive. Amazon can get you 80% of the way there, 70% of the way there but if you're like, an AI developer, you're a CMO, you're a marketing developer, you kind of want this end to end solution. So, how can I put together a full suite of tools from beginning to end that can give me a product that's a better experience. So, either I have something that's a deeper IP play a seam between multiple Clouds or give it end to end solutions around a problem and solve that one problem for our customer. >> And in most cases, the underlay is Amazon or Azure. >> Or Google or Alley Cloud or On Premises. Not going to wait any time soon, right? And so, how do I create a single fabric, if you will that looks similar? >> I want to riff with you in real time here on theCUBE around data. So, data scale is obviously a big discussion that's starting to happen now, data tsunami, we've heard that for years. So, there's two scale benefits, horizontal scale with data and then vertical specialism, vertical scale or ya know, using AI machine learning in apps, having data, so, how do you view that? What's your reaction to the notion of creating the horizontal scale value and vertical specialism value? >> Both are a great place for startups, right? They're not mutually exclusive but I think if you go horizontal, the amount of data being created by your applications, your infrastructure, your sensors, time stories data, ridiculously large amount, right? And that's not going away any time soon. I recently did investment in ChronoSphere, 'cause you guys covered over at CUBEcon a few weeks ago, that's talking about metrics and observability data, time stories data. So, they're going to handle that horizontal amount of data, petabytes and petabytes, how can we quarry this quickly, deeply with a lot of insight? That's one play, right? Cheaper, better, faster at scale. The next play, like you said, is vertical. It's how do I own data or slice the data with more contacts than I know I was going to have? We talked about the virtual cycle of data, right? Just the system of intelligence, as well. If I own a set of data, be it healthcare, government or self-driving car data, that no one else has, I can build a solution end to end and go deep and so either pick a lane or pick a geography, you can go either way. It's hard to do both, though. >> It's hard for startup. >> For a startup. >> Any big company. >> Very few companies can do two things well, startups especially, succeed by doing one thing very well. >> I think my observation is that I think looking at Amazon, is that they want the horizontal and they're leaving offers on the table for our startups, the vertical. >> Yeah, if you look at their strategy, the lower level Amazon gets, the more open-sourced, the more ubiquitous you try to be for containers, server lists, networking, S3, basic sub straits, so, horizontal horizontal, low price. As you get higher up from like, deep mind like, AI technologies, perception, prediction, they're getting a little bit more specialized, right? As you see these solutions around retail, healthcare, voice, so, the higher up in the stack, they can build more narrow solutions because like any startup of any product, you need the right wedge. What's the right wedge in the customers? At the base level of developers, building blocks, ubiquitous. For solutions marketing, healthcare, financial services, retail, how do I find a fine point wedge? >> So, the old Venture business was all enamored with consumers over the years and then, maybe four years ago, Enterprise got hot. We were lowly Enterprise guys where no one-- >> Enterprise has been hot forever in my mind, John but maybe-- >> Well, first of all, we've been hot on Enterprise, we love Enterprise but then all of a sudden, it just seemed like, oh my God, people had an awakening like, and there's real value to be had. The IT spend has been trillions and the stats are roughly 20 or so percent, yet to move to the Cloud or this new next gen architecture that you're investing companies in. So, a big market... that's an investment thesis. So, a huge enterprise market, Steve Malaney of Aviation called it a thousand foot wave. So, there's going to be a massive enterprise money... big bag of money on the table. (laughs) A lot of re-transformations, lot of reborn on the Cloud, lot of action. What's your take on that? Do you see it the same way because look how they're getting in big time, Goldman Sachs on stage here. It's a lot of cash. How do you think it's going to be deployed and who's going to be fighting for it? >> Well, I think, we talked about this in the past. When you look to make an investment, as a startup founder or as a VC, you want to pick a wave bigger than you, bigger than your competitors. Right so, on the consumer side, ya know, the classic example, your Instagram fighting Facebook and photo sharing, you pick the mobile first wave, iPhone wave, right, the first mobile native photo sharing. If you're fighting Enterprise infrastructure, you pick the Cloud data wave, right? You pick the big data wave, you pick the AI waves. So, first as a founder startup, I'm looking for these macro-waves that I see not going away any time soon. So, moving from BaaS data to streaming real time data. That's a wave that's happening, that's inevitable. Dollars are floating from slower BaaS data bases to streaming real time analytics. So, Rocksett, one of the investors we talked about, they're riding that wave from going BaaS to real time, how to do analytics and sequel on real time data. Likewise, time servers, you're going from like, ya know, BaaS data, slow data to massive amounts of time storage data, Chronosphere, playing that wave. So, I think you have to look for these macro-waves of Cloud, which anyone knows but then, you pick these small wavelettes, if that's a word, like a wavelettes or a smaller wave within a wave that says, "Okay, I'm going to "pick this one trend." Ride it as a startup, ride it as an investor and because that's going to be more powerful than my competitors. >> And then, get inside the wave or inside the tornado, whatever metaphor. >> We're going to torch the metaphors but yeah, ride that wave. >> All right, Jerry, great to have you on. Seven years of CUBE action. Great to have you on, congratulations, you're VIP, you've been with us the whole time. >> Congratulations to you, theCUBE, the entire staff here. It's amazing to watch your business grow in the past seven years, as well. >> And we soft launch our CUBE 365, search it, it's on Amazon's marketplace. >> Jerry: Amazing. >> SaaS, our first SaaS offering. >> I love it, I mean-- >> John: No Venture funding. (laughs) Ya know, we're going to be out there. Ya know, maybe let you in on the deal. >> But now, like you broadcast the deal to the rest of the market. >> (laughs) Jerry, great to have you on. Again, great to watch your career at Greylock. Always happy to have ya on, great commentary, awesome time, Jerry Chen, Venture partner, general partner of Greylock. So keep coverage, breaking down the commentary, extracting the signal from the noise here at reInvent 2019, I'm John Furrier, back with more after this short break. (energetic electronic music)

>> Narrator: Live from San Diego, California, it's theCUBE covering KubeCon and CloudNativeCon. Brought to you by Red Hat, the CloudNative Computing Foundation and its ecosystem partners. >> Docker, Docker, Docker. No, you're in the right place. This is KubeCon CloudNativeCon 2019 here in San Diego. I'm Stu Miniman kicking off three days of live, wall to wall coverage. My co-host for most of the week this week is John Troyer. Justin Warren's also in the house. He'll be hosting for me. And a big shout out to John Furrier who's back at the corporate ranch in Palo Alto keeping an eye on all the CloudNative stuff with us. The reason that I actually mentioned Docker is because it is the first thing that is on our lips this week. Just this week, Docker, which is the company that, if it wasn't for Docker, we wouldn't have 12,500 people here at this event. Really democratized containers. But the company itself built out a platform, millions and millions of companies using containers. But when the orchestration layer came in there was some contention, there's lots of politics. I'm waiting for Docker the Broadway musical to come out to talk about all the ins and outs there because Kubernetes really sucked the air out of the CloudNative world. Spawned tons of projects here. As you can see behind us, this ecosystem is massive and swelling. Last year it was 8,000 people, year before it was 4,000 people, so many people here, so. And John, so, let's start. This is your first time at this show, you've done many shows with us, definitely covered some of the cloud-native, you've worked with many of the companies that are in this ecosystem here. Give me your first impressions here of KubeCon CloudNativeCon. >> Sure, sure. Well, I mean Stu, 12,000 people, it's pretty crowded here. We're right by the t-shirt line, on day one of the conference. Look, a conference this big, especially an open source conference, there's several jobs to be done, right. This is an active set of open source projects and open source communities. So a lot of the keynote this morning was updating people on details about the latest releases, the latest features, what's in, what's out, what's going on. CNCF is a very broad umbrella for a very broad number of projects, not a coherent opinionated stack, it's a lot of different things that all contribute to a set of CloudNative technologies. So, that's job one. Job two, it's a trade show, and it's an industry show, and people are coming here to figure out how to build and learn and operate. So, that wasn't particularly well served by the keynote this morning. There was certainly a lot of hands-on this week. There's a huge number of breakouts, there's a huge number of tracks. Even day zero, which is a set of specialty breakout workshops and sessions, everything was packed. There were over a dozen of those. So, what strikes me is the breadth here is that it's a mile wide. I won't say it's an inch deep, because there's some, but it is a mile wide. >> Yeah, yeah, John you are right, there's so much going on. The day zero tracks are amazing. I think there were over two dozen, maybe even more of the sessions where, you know, half-day or full day deep dives. Even talk, there was some other small events even that went on for two or three days leading up to this. So, sprawling ecosystem. Last year at this show in Seattle, I actually said that this show is the independent cloud show that we've been looking for. John, I was at Microsoft Ignite just a couple of weeks ago, and absolutely, Satya Nadella, they're not talking about the bits and the bytes. It's a, you know, Microsoft is your trusted partner for everything you're going to do, including building 50 billion new applications. Amazon Reinvent will just be right after Thanksgiving, and we will hear a very different message from Amazon and where they play. But this is not a company, it is a lot of different projects. The CNCF is the steward of this, and so Kubernetes is the one that gets all the attention. I think for this group to even grow more, it needs to be focused more on the CloudNativeCon, because how do we do cloud-native? You know, what does that mean? We heard, you know, Sugu was up on stage talking about Vitess, and he said, look, if you bake your database directly in fully Kubernetes cloud-native, that means that when you want to move between clouds you bring your data with you. So, data, security, networking, messaging, there's so many pieces here. It's a lot of work to be done to mature this stack, but it definitely is getting more mature. You start hearing many of these projects with a million or more downloads a month. So many pieces. John, what are you looking to dig into this week, what are you most excited for, what questions do you want answered? >> Well, here on theCUBE I'm always excited when we get to talk to people in production, customers, really see what's going on. There's a lot of stuff in production right now, which is not to say a lot of stuff isn't bleeding edge, right. I hear a lot of stuff, just out of the woodwork, about things that are fragile, things that aren't ready, things that are not quite updated, and I think Kubernetes is an architectural as well as a spiritual home for everything. But there's a lot of pieces that plug in, and there are opinionated ways of doing it, there are best of breed way, there are vertically integrated stacks. What's the best approach, it's not clear to me. I mean if you have to look at it from a company perspective, who are the winners and losers, I don't think that's a very productive way of looking at it. I'm interested in some projects like, we're going to be talking with Rancher, and they've got some announcements, but I'm also interested in K3s, which is their project there. I'm been hearing some really interesting things on the storage front. You know, all these things are really necessary. It's not all just magic containers moving around. You got to actually get the bits and bytes into the right place at the right time and backed up. >> Yeah, I love that you brought up K3s. Edge is definitely something that I hear talking a lot, because if you talk about cloud-native, it's not just about public cloud. Many of these things can run in my on-premises data centers and everything like that. >> And Edge fits in all of these environments, so. Right, winners and losers, I remember two years ago, first time I got a chance to interview Kelsey Hightower, who we do have on the program. He had actually taken a couple shows off, but he's back here at the show. I said Kelsey, why are we spending so much talking about Kubernetes? Doesn't this just get baked into every platform? And he's like, yeah totally, that's not the importance of it. It's not about distributions, and not about who's who, any of the software companies, it's how do they pull all of the pieces together. How do they add value on top of it. One of the terms I've heard mentioned a lot is, we need to think a lot about day two. Heck, there was even one of the companies that was heavy in this space, Mesosphere, they renamed the company Day Two IQ, spelled D2IQ. No relation to R2D2. But you know, that's what they are focused on to help these things really go together. So yeah, we talk about multicloud, and how do I get my arms around all of these pieces, how do I manage a sprawling environment. You add Edge into it. I've got a huge surface of attack for security issues. So, John, remember cloud was supposed to be simple and cheap, and it really isn't either of those things anymore, so yeah, a lot for us to dig into. >> Yeah, it'll be an interesting mix. Developers, experts, people brand new, probably half the people here they're the first time, and people coming over from the IT space as well as people coming from the open source space and I even saw this morning this is the biggest conference I've ever been to. So it's a many, it's different parts of the elephant, I'd say. >> Yeah, absolutely. It is a good sized conference, especially for open source it probably is the largest. But Salesforce Dreamforce is going on this week, which is more than an order of magnitude bigger, so my condolences to anybody in San Francisco right now, because we know the BART and everything else completely swamped with too many people. One other thing, you know, CNCF, what's really interesting for me always is when you look at a lot of these projects, the people that we saw up on stage were companies, it was the person that oh, I started this project and I'm the technical lead on it, and that's where I'm going. We've interviewed many of the people that start these projects, and they come many times out of industry. It's not a vendor that said, hey, I built something and I'm selling it. It is companies like Uber and Lyft that said, we did things at massive scale, we had a problem, we built something, we thought it was useful for us. Open source seemed a good way to help us get broader visibility and maybe everybody could help, and other people not only pitch in, but say this is hugely valuable, and that's where we go with it. So, it's something we, a narrative I've heard for years about everybody's going to be a software company, well, almost everybody at this conference is building software. We've heard about 30 to 40% of the people attending this show are developers, and therefore many of them are going to build products. A question I have and I'll give you is, with Docker, we just kicked off talking about Docker. You know, Docker created this huge wave of what happens there, but to put it bluntly, Docker the business failed. So, they are not dead, there's the piece that's in Mirantis, there's the piece doing the developer piece. We wish all of them the best of luck, but they had the opportunity to be the next VMware, and instead they are the company that gave us this wave, but did not capitalize on it. So, I look around and I see so many companies, and you say, "Hey, what are you?" "Oh, we're the creators of X technology in this project," and my question is, are you actually going to be able to make money and do a business, or is this just something that gets fit into the overall ecosystem. John, any thoughts and advice for those kind of companies. >> Well, I mean we are here, even though there's 12,000 people here, this is still very leading edge, right. There's a lot of pieces, parts here. We're not sure how they're all going to fit together. A lot of the projects have come out of real use cases, like you say, but they're, it's commercial viability is a different beast than utility. Docker was very good at developer experience, but the DNA of actually selling an enterprise management stack is a whole different beast, and there are a lot of those too. So I mean I think a lot of the companies here may not be around, but their technologies will live on. I think if you're here, and the interviews here at the show I think will be a, you'll want to have your antenna out to see like, okay, does this give you a feeling like this is solving a real problem and is incorporated in a real ecosystem. You know, the big company, it cuts both ways, right. Some of the times those technologies get absorbed and become the standard, sometimes they disappear. So the advice is you just put one foot in front of the other and try to find people in production. That's the only way at the end of the day that you could move ahead as a small company. >> All right, John, I gave you one piece of advice when we came here and I said, you know one thing we don't talk about at this show, we don't talk about OpenStack. So, I'm going to break that rule for a second here, just 'cause I feel we have as an industry learned some of the lessons. There is some of the irrational exuberance around some of these. There's lots of money being thrown at these environments, but I do feel that we are reaching maturity and adoption so much faster, because we are not trying to replacing something. The early days of OpenStack was, you know, we're your alternative for AWS, and we're going to get you off of VMware licensing. And both of those things were, they didn't happen for the most part. And OpenStack did fit in certain environments, especially outside of North America there's lots of OpenStack deployments. The telecommunications environment OpenStack is used a bunch. Telecom, another area, talk about Edge, that plays in here and we have a number of conversations. But there are both the big and the small companies when I look at our list of people we're going to be talking on the program. You know, I love first the customers. We've got Fidelity, Bloomberg, Red Cross, and Ford Motor Company all on the program, and we've got big companies, mega giants like Cisco, Hewlett Packard Enterprise, as well as couple of companies that came out of stealth like in the last week, including Render and Chronosphere. So, you know, broad spectrum of what's going on. You've done some of the OpenStack shows with me. You've got a long community and ecosystem viewpoint, John. What do you think and what do you hear, yeah. >> You know, this is, I guess yeah, this is a next generation, you could look at it that way. Anytime you bring together one of these open source foundations, you know, it is kind of a new style of development. You do have differing agendas. People do again have to have their antenna up to see, is this person promoting this open source project and what is their commercial interest in it. Because there are different agendas here. But it looks pretty healthy. Look, there's probably a million engineers worldwide that are going to have to know the guts of Kubernetes, but it's a different job to be done than OpenStack. OpenStack community is actually, that exists, is still thriving. It is good for the job to be done there. This job to be done's a little different. I think it's going to be an engine, you know, the engine that's embedded in everything else. So there's going to be a hundred million engineers that don't need to know anything about Kubernetes, but people here are the people that pop the hood open and start to you know, mess with the carburetor and this is a carburetor show. And so for the coverage here we're going to try to up level it to talk about the business a little bit, but this feels important. It feels cross-cloud, it feels outside of any one silo, and I'm really interested to see what we're going to learn this week. >> Okay, and thank you John. I really appreciate it to get it right final. It's like what is our job here? We are an independent media organization. Yes, we did bring our own stickers here to be able to, you know, we know everybody here loves stickers, so we've got theCUBE and we've got the fun gopher one, our friends at Women Who Go that support this, because, you know, inclusion, diversity, something that this community definitely embraces, we are huge supporters of their, but right, we want to be able to give that broad viewpoint of everything. We're not going to be able to get into every project. We're not going to go as deep as the day zero content web, but give a good flavor for everything going on in the show. I've found of all the shows I've gone to in recent years, this is some of the biggest brains in the industry. There's a lot of really important stuff, so I appreciate bringing my PHD holding co-host with me, John. Looking forward to three days with you to dig into all the environment. All right, so we will be wall to wall coverage, three days. If you're at the event, we are here in the expo hall. You can't miss us, we've got the big lights right next to the CloudNativeCon store. If you're online of course reach out to us. I'm @stu, S-T-U on Twitter. He's @jtroyer, and hit us up, see us in person, come grab some stickers, let us know who you want to talk to and what question you have, and as always, thank you for watching theCUBE. (upbeat music)