(bright music) >> Hello everyone and welcome back to theCUBE's live coverage here in San Francisco, California for AWS Summit 2022. I'm John Furrier, your host of theCUBE. Two days of coverage, AWS Summit 2022 in New York city's coming up this summer, we'll be there as well. Events are back. theCUBE is back. Of course, with theCUBE virtual, CUBE hybrid, the cube.net. Check it out, a lot of content this year more than ever. A lot more cloud data, cloud native, modern applications, all happening. Got a great guest here. Jeremy Burton, CUBE alumni, CEO of Observe, Inc. in the middle of all the cloud scale, big data, observability. Jeremy, great to see you. Thanks for coming on. >> Always great to come and talk to you on theCUBE man. It's been a few years. >> Well, you got your hands. You're in the trenches with great startup, good funding, great board, great people involved in the observability space, hot area, but also you've been a senior executive. President of Dell, EMC, 11 years ago you had a vision and you actually had an event called cloud meets big data. >> Jeremy: Yeah. >> And it's here. You predicted it 11 years ago. Look around, it's cloud meets big data. >> Yeah, the cloud thing I think was probably already a thing, but the big data thing I do claim credit for sort of catching that bus early, We were on the bus early and I think it was only inevitable. Like if you could bring the economics and the compute of cloud to big data, you could find out things you could never possibly imagine. >> So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved. The board level, the founders, the people there, cloud, Amazon, what's going on here? You're doing a startup as the CEO at the helm, chief of Observe, Inc., which is an observability, which is to me in the center of this confluence of data, engineering, large scale integrations, data as code, integrating into applications. It's a whole another world developing, like you see with Snowflake, it means Snowflake is super cloud as we call it. So a whole nother wave is here. What's this wave we're on? How would you describe the wave? >> Well, a couple of things. People are, I think, riding more software than ever before. Why? Because they've realized that if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think more applications now than any point, not just ever, but the mid nineties. I always looked at as the golden age of application development. Now, back then people were building for Windows. Well now they're building for things like, AWS is now the platform. So you've got all of that going on. And then at the same time, the side effect of these applications is they generate data and lots of data and the transactions, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can I understand who my best customers are? What I sell today? If people came to my website and didn't buy, then why not? Where did they drop off? All of that they want to analyze. And the answers are all in the data. The question is, can you understand it? >> In our last startup showcase, we featured data as code. One of the insights that we got out of that, and I want to get your opinion on or reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse, and then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more effort to say, let's go look at the data, 'cause now machine learning is getting better. Not just train once, they're iterating. This notion of iterating and then pivoting, iterating and pivoting That's a Silicon Valley story. That's like how startups were, but now you're seeing data being treated the same way. So now you have this data concept that's now part of a new way to create more value for the apps. So this whole new cycle of data being reused and repurposed, then figure it out. >> Yeah, yeah, I'm a big fan of, years ago, just an amazing guy, Andy McAfee, at the MIT labs. I spent time with and he had this line, which still sticks to me this day, which is look, he said, I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And this has going back 10 years when he was saying these kind of things and certainly, research is on the forefront. But I think starting to see that mindset of the MIT research be mainstream in enterprises. They're realizing that, yeah, it is about the data. If I can better understand my data better than competitor, then I've got an advantage. And so the question is how? What technologies and what skills do I need in my organization to allow me to do that? >> So let's talk about Observe, Inc. You're the CEO. Given you've seen the waves before, you're in the front lines of observability, which again is in the center of all this action. What's going on with the company? Give a quick minute to explain Observe for the folks who don't know what you guys do. What's the company doing? What's the funding status? What's the product status? And what's the customer status? >> Yeah, so we realized, a handful of years ago, let's say five years ago. Look, the way people are building applications is different. They're way more functional. They change every day. But in some respects there are a lot more complicated. They're distributed, microservices architectures. And when something goes wrong, the old way of troubleshooting and solving problems was not going to fly because you had so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So that's observability. It's actually a term that goes back to the 1960s. It was, a guy called, like everything in tech, it's a reinvention of something from years gone by, but there's a guy called Rudy Coleman in 1960s, kind of term. And the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for the best part of four years now. It took us three years just to build the product. I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You need a lot of functionality to have something that's credible with a customer. So yeah, this last year, we did our first year selling. We've got about 40 customers now. We got great investors Sutter Hill Ventures. Mike Speiser who was really the first guy in the Snowflake and the initial investor. We're fortunate enough to have Mike on our board. And part of the Observe story is closely knit with Snowflake because all of that telemetry data, we store in there. >> So I want to pivot to that. Mike Speiser, Snowflake, Jeremy Burton, theCUBE kind of same thinking. This idea of a super cloud or what Snowflake became. >> Jeremy: Yeah. >> Snowflake is massively successful on top of AWS. And now you're seeing startups and companies build on top of Snowflake. >> Jeremy: Yeah. >> So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, like as Jerry Chen in Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with Snowflake's. So as a startup, what's your view on building on top of say a Snowflake or an AWS, because again, you got to go where the data is. You need all the data. >> Jeremy: Yeah. >> What's your take on that? >> Having enough gray hair now. Again, in tech, I think if you want to predict the future, look at the past. And 20 years ago, 25 years ago, I was at a smaller company called Oracle. And an Oracle was the database company and their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms. One, Windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And then that was the ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years, gray hairs, the platform isn't the operating system anymore. The platform is AWS, Google cloud. I probably look around if I say that in. >> It's okay. But Hyperscale. >> Yeah. >> CapEx built out. >> That is the new platform. And then Snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say the big data world, what Oracle did for the relational data world way back 25 years ago. And then there are folks like us come along and of course my ambition would be, look, if we can be as successful as an SAP building on top of Snowflake, as they were on top of Oracle, then we'd probably be quite happy. >> So you're building on top of Snowflake? >> We're building on top of Snowflake a hundred percent. And I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that's a risk. >> Are you still on the board? >> Yeah, I'm still on the board. Yeah. That's a risk I'm prepared to take. I am long on Snowflake. >> It sounds, well, you're in a good spot. Stay on the board then you'll know as going on. Okay, seriously, this is a real dynamic. >> Jeremy: It is. >> It's not a one off. >> Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS, it is an order of magnitude more than Microsoft was 25 years ago with windows. And so I believe the opportunity for folks like Snowflake and folks like Observe, it's an order magnitude more than it was for the Oracle and the SAPs of the old world. >> Yeah, and I think this is something that this next generation of entrepreneurship is the go big scenario is you got to be on a platform. >> Yeah and it's quite easy. >> Or be the platform, but it's hard. There's only like how many seats are at that table left. >> Well, value migrates up over time. So when the cloud thing got going, there were probably 10, 20, 30, rack space and there's 1,000,001 infrastructure for service, platform as a service. My old employee EMC, we had Pivotal. Pivotal was a platform as a service. You don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to extract a real business, you got to move up, you got to add value, you got to build databases, then you got to build applications. >> It's interesting. Moving from the data center to the cloud was a dream for starters 'cause they didn't have to provision the CapEx. Now the CapEx is in the cloud. Then you build on top of that, you got Snowflake. Now you got on top of that. >> The assumption is almost that compute and storage is free. I know it's not quite free. >> Yeah, it's almost free. >> But as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've got to get into. >> And I think the platform enablement to value. So if I'm an entrepreneur, I'm going to get a serious multiple of value in what I'm paying. Most people don't even blink at their AWS bills unless they're like massively huge. Then it's a repatriation question or whatever discount question. But for most startups or any growing company, the Amazon bill should be a small factor. >> Yeah, a lot of people ask me like, look, you're building on Snowflake. You're going to be paying their money. How does that work with your business model? If you're paying them money, do you have a viable business? And it's like, well, okay. We could build a database as well in Observe, but then I've got half the development team working on something that will never be as good as Snowflake. And so we made the call early on that, no, we want to innovate above the database. Snowflake are doing a great job of innovating on the database and the same is true with something like Amazon, like Snowflake could have built their own cloud and their own platform, but they didn't. >> Yeah and what's interesting is that Dave Vellante and I have been pointing this out and he's obviously more on Snowflake. I've been looking at Databricks and the same dynamics happening. The proof is the ecosystem. >> Yeah. >> If you look at Snowflake's ecosystem right now and Databricks, it's exploding. The shows are selling out. This floor space is booked. That's the old days at VMware. The old days at AWS. >> One and for Snowflake and any platform provider, it's a beautiful thing because we build on Snowflake and we pay their money. They don't have to sell to us. And we do a lot of the support. And so the economics work out really, really well if you're a platform provider and you've got a lot of ecosystems. >> And then also you get a trajectory of economies of scale with the institutional knowledge of Snowflake, integrations, new products, you're scaling and step function with them. >> Yeah, we manage 10 petabytes of data right now. When I arrived at EMC in 2010, we had one petabyte customer. And so at Observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so being able to rely on a platform that can manage that is invaluable. >> Well, Jeremy, great conversation. Thanks for sharing your insights on the industry. We got a couple minutes left, put a plug in for Observe. What do you guys do? You got some good funding, great partners. I don't know if you can talk about your POC customers, but you got a lot of high ends folks that are working with you. You get in traction. >> Yeah >> Scales around the corner sounds like. Is that where you at? Pre-scale? >> We've got a big announcement coming up in two or three weeks. We've got new funding, which is always great. The product is really, really close. I think, as a startup, you always strive for market fit, at which point can you just start hiring salespeople and the revenue keeps going. We're getting pretty close to that right now. We've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, which is our sweet spot to begin with, but we're starting to get some really interesting enterprise type customers. We're F5 networks. We're POC in right now with Capital One. We've got some interesting news around Capital One coming up. I can't share too much, but it's going to be exciting. And like I said, Sutter Hill continue to stick. >> And I think Capital One's a big Snowflake customer as well, right? >> They were early and one of the things that attracted me to Capital One was they were very, very good with Snowflake early on and they put Snowflake in a position in the bank where they thought that snowflake could be successful. And today that is one of Snowflake's biggest accounts. >> Capital One, very innovative cloud. Obviously, AWS customer and very innovative. certainly in the CISO and CIO. On another point on where you're at. So you're pre-scale meaning you're about to scale. >> Jeremy: Right. >> So you got POCs. What's that trajectory look like? And you see around the corner, what's going on? What's around the corner that you're going to hit the straight and narrow and gas it fast? >> Yeah, the key thing for us is we got to get the product right. The nice thing about having a guy like Mike Speiser on the board is he doesn't obsess about revenue at this stage. His questions at the board are always about like, is the product right? Is the product right? Have you got the product right? 'Cause we know when the product's right, we can then scale the sales team and the revenue will take care of itself. So right now all the attention is on the product. This year, the exciting thing is we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the New Relics and AppDynamics, the last generation of APM tools. You're going to be able to do that within Observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one 'cause we complete the trifecta, the logs. >> What's the secret sauce of observe if you put it into a sentence, what's the secret sauce? >> I think, an amazing founding engineering team, number one. At the end of the day, you have to build an amazing product and you have to solve a problem in a different way and we've got great long term investors. And the biggest thing our investors give is, actually it's not just money, it gives us time to get the product right. Because if we get the product right, then we can get the growth. >> Got it. Final question while I got you here. You've been on the enterprise business for a long time. What's the buyer landscape out there? You got people doing POCs, Capital One scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Obviously, we're seeing people go in and dip into the startup pool because new ways to refactor their business, restructure. So a lot of happening in cloud. What's the criteria? How are enterprises engaging in with startups? >> Yeah, enterprises, they know they've got to spend money transforming the business. I almost feel like my old Dell or EMC self there, but what we were saying five years ago is happening. Everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or take a bet on new technology in order to help them do that. So I think you've got buyers that A, have money, B, are prepared to take risks, and it's a race against time to get their offerings in this new digital footprint. >> Final, final question. What's the state of AWS? Where do you see them going next? Obviously, they're continuing to be successful. How does cloud 3.0? Or they always say it's day one, but it's maybe more like day 10, but what's next for AWS? Where do they go from here? Obviously, they're doing well and they're getting bigger and bigger. >> Yeah, it's an amazing story. We are on AWS as well. And so I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They have an early leads. And if you look at where, maybe the likes of Microsoft lost the plot in the late nineties, it was they stopped really caring about developers and the folks who are building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they have an amazing head start. And if they did more, if they do more than that, that's what's going to keep this juggernaut rolling for many years to come. >> They got the Silicon and they got the Stack developing. Jeremy Burton inside theCUBE, great resource for commentary, but also founding with the CEO of a company called Observe, Inc. In the middle of all the action and the board of Snowflake as well. Great startup. Thanks for coming on theCUBE. >> Always a pleasure. >> Live from San Francisco's theCUBE. I'm John Furrier, your host. Stay with us. More coverage from San Francisco, California after the short break. (soft music)

(upbeat music) >> Welcome to theCUBE and our Q3 AWS Startup Showcase. I'm Lisa Martin. I've got two guests here with me, Erez Berkner is back, the Co-Founder and CEO of Lumigo. Hey, Erez, good to see you. >> Hey, Lisa, great to be here again. >> And Kevin O'Neill, the CTO at Flex is here as well. Kevin, welcome. >> Hi, Lisa, nice to meet you. >> Likewise, we're going to give the audience an overview of Lumigo and Flex. Let's go ahead, Erez, and start with you. Talk to us about Lumigo, and I think you have a slide to pull up to walk us through? >> Yeah, I have a couple, so, great to be here again. And just as an overview, Lumigo is a serverless monitoring and debugging platform. Basically allowing the user, the developer to get an end-to-end view of every transaction in his cloud. It's basically distributed tracing that allows you from one hand to monitor, to see a visual representation of your transaction, but also allows you to drill down and debug the failure to get to the root cause. So essentially, once you have the visualization and if we'll move to the next slide, you can actually click and drill down and see all the relevant debug information like environment variables, duct rays, inputs, outputs, and so on and so forth. And by that, understanding the root cause. And sometimes those root causes of the problems are not just errors, they are latencies, they are hiccups. And for that, we can see on the next slide, where Lumigo allows you to see where do you spend your time? Where are the hiccups in your system? What's running in Paula to what in the same transaction, where you can optimize. And that's the essence of what Lumigo provides in a distributed environment and focusing on serverless. >> Got it, focusing on serverless, we'll dig into that in a second. Kevin, give us an overview of Flex. You're a customer of Lumigo? >> We are indeed. So Flex is a build smoothing platform. We help people pay their rent and other bills, in these times of uncertainty and cashflow, the first of the month for your rent, it's a big bill. Being able to split that up into multiple payments is a lot easier. And when we entered the market, you were looking at a place where people were using things like payday loans, which are just ridiculous, really hurting, hurt people in the longterm. So we want to come in with something that is a little more equitable, little fairer and help people who can well afford their rent. They just can't afford it on the first, right? And so we started with rent, and now we cover all the bills like utilities and things like that. >> What a great use case, and I can't even imagine, Kevin, in the last year and a half, how helpful that's been as the world has been so dynamic. So talk to me a little bit about what you were doing before Lumigo and we'll get into then why you went the serverless route. >> Right, so I came to Flex to help them out with some problems that we're having as our servers were scaling up. Obviously, when the business hit, it was really, it went from zero to 100 miles an hour so quickly. And so I came in to help sort out some of the growing issues. And so when I started looking at that, we were three developers and didn't want to spend time on ops, didn't want to spend time on all of the things that you have to do just to be in business, right? And it's really expensive in the technical space. If you get into something about Kubernetes or things like that, you spend a lot of time building that infrastructure, making sure, and that's really minimal value to your business. It's there for reliability, but it doesn't really focus in on the thing that is important to you. So we wanted to build something that minimized that, we talk about DevOps, we want it ops zero, right? So that's like DevOps is a really nice practice, but having people in that role, it seems like you're still doing ops, right? You still got people who are doing those things, and we want it to kind of eliminate that. So I had some experience with serverless before joining Flex. I thought we'll run up a few things and spike up a few things. When you come out of environments like Kubernetes or your more traditional AC to type infrastructure, you'd lose some things. And one of the big things you'd lose is platforms of visibility. So things like OpenTrace and Datadog, and things like that, that do these jobs of telling you what's going on in your infrastructure, you've got fairly complex infrastructure going on, lots of things happening. And so, we initially started with what was available on the platforms, right? So we started with your CloudWatch logs and New Relics, right? Which got us somewhere. But as soon as we started to get into more complex scenarios where we're talking across multiple hops, so through SQS and then through EventBridge and Dynamo, it was very difficult to be able to retrace a piece of information. And that's when we started looking around for solutions, we looked at big traditional pliers, the Datadogs, the New Relics and people like that. And then the serverless specific players, and we ended up landing on Lumigo, and I couldn't have been happier with the results, from day one, I was getting results. >> That's great, I want to talk about that too, especially as you say, we wanted to be able to focus on our core competencies and not spend time in resources that we didn't have in areas where we could actually outsource. So I want to go back to Erez, talk to me about some of the challenges that Kevin articulated, are those common across the board, across industries that Lumigo sees? >> Yeah, I think the main thing when we met Kevin main were about visibility and about ability to zoom out, see the bigger picture and when something actually fails or about to fail in production, being able to drill down to understand what happened, what is the root cause, and go ahead and fix it instead of going through different CloudWatch logs, and log groups and connecting the dots manually. And that's one of the most common challenges when enterprise, where software engineers are heading toward serverless, toward managed services. So, definitely we'll hear that it was many of our customers. >> So Kevin, talk about the infrastructure that you've set up with serverless and go through some of the main benefits that Flex is getting. >> Right, so look, the day one thing of course, is the number of people we need doing operations as we've grown is next to nothing, right? We are able to create in that, we all want this independence of execution, right? So as you scale, I think there's two ways really to scale a system, right? You can build a monolith and shot it, that works really, really well, right? You can just build something that just holds a ton of data and everything seems connected when you release it all in one place, or you build something that's a little more distributed and relies on asynchronous interactions effectively, like in everywhere but the edges, both of those things scale. The middle ground doesn't scale, right? That middle ground of synchronous systems talking to synchronous systems, at some point, your lightency is your sum of all the things you're talking to, right? So doing anything in a quick way is not possible. So when we started to look at things like, I'm sorry, so the other challenge is things like logging and understanding what's happening in your system. Logging is one of those things that you always don't have the thing logged that you're interested in, right? You put in whatever logging you like, but the thing you need will always be missing, which is why we've always taken a tracing approach, right? Why you want to use something like Lumigo or an OpenTrace, you don't sit there and say, "Hey, log this specifically," you log the information that's moving through the system. At that point, you can then look at what's happening specifically. So again, the biggest challenge for us is that we run 1500 landlords, right? We run 600 queues. There's a lot of information. We use an EventBridge, we use Dynamo, we use RDS, we've got information spread out. We moved stuff, but to third party vendors, we're talking out to say, two guys like Stripe and Co, and we're making calls out of those. And we want to understand when we've made those calls, what's the latency on those calls. And for a given interaction, it might touch 20 or 30 of those components. And so for us, the ability to say, "Hey, I want to know why this file to write down here." We need to actually look through everywhere, explain, and understand how it's complex, right? Where this piece of data that was wrong come from? And so, yeah, which is difficult in a distributed environment where your infrastructure is so much a part of somebody else's systems, you don't have direct access to assistance. You'd only got the side effects of the system. >> Right, so talk to me in that distributed environment, Kevin, how does Lumigo help to improve that? Especially as we're talking about payments and billing and sensitive financial information. >> Right, so in a couple of ways, the nice part about Lumigo is I really don't have to do much in order for it to just do its thing, right? This comes back to that philosophy of zero ops, right? Zero effort. I don't want to be concentrating on how I build my tracing infrastructure, right? I just want it to work. I want it to work out of the box when something happens, I want it to have happened. So Lumigo, when I looked at it, when I was looking at the platforms, the integration's so straightforward, the cost integration being straightforward is kind of useless, if it doesn't actually give you the information you want. And we had a challenge initially, which was, we use a lot of EventBridge, and of course, nothing tries to EventBridge until we got, I mentioned this to Erez and Co, and said, "Hey guys, we really need to try to EventBridge, and a little while later, we were tracing through EventBridge, which was fantastic. And because I would say 70% of our transactions evolve something that goes through EventBridge, the other thing there. We're also from an architectural standpoint, we're also what's known as an event source system. So we derive the state of the information from the things that have occurred rather than a current snapshot of what something looks like, right? So rather than you being Lisa with a particular phone number and particular email address stored in a database as a record, you are, Lisa changed the phone number, Lisa changed her email address. And then we take that sequence of things and create a current view of Lisa. So that also helps us with ordering, right? And at those lower levels, we can do a lot of our security. We can do a lot of our encryption, we can say that this particular piece of information, for example, a social security number is encrypted and never is available as plain text. And you need the keys to be able to unlock that particular piece of information. So we can do a lot of that, a lower level infrastructure, but that does generate a lot of movement of information. >> Right. >> And if you can't trace that movement of information, you're in a hurting place. >> So Erez, we just got a great testimonial from Kevin on how Lumigo's really fundamental to their environment and what they're able to deliver to customers, and also Kevin talked about, it sounds like some of the collaboration that went on to help get that EventBridge. Talk to me, Erez, about the collaborative partnership that you have with Flex. >> Yeah, so I think that it's more of a, I would say a philosophy of customers, the users come first. So this is what we're really trying to about. We always try to make sure there's an open communication with all of our customers and for us customer is a key and user's a key, not even a customer. And this is why we try to accommodate the different requests, specifically on this event, this was actually a while after AWS released the service and due to the partnership that we have with AWS, we were able to get this supported relatively fast and first to market supporting EventBridge, and connecting the dots around it. So that's one of the things that we really, really focused on. >> Kevin, back to you, how do you quantify the ROI of what Lumigo is delivering to Flex? >> That's a really good question. And Erez, and I've talked about this a few times, because the simple fact is if I add up the numbers, it costs me more to trace than it does to execute. But if I look at the slightly bigger picture, I also don't have op stuff, right? And I also have an ability to look at things very quickly. The service cost is nothing compared to what I would need if I was running my own tracing through OpenTrace with my own database, monitor the staff to support those things. But the management of those things, the configuration of those things, the multiple touchpoints I'd need for those things, they're not the simple thing. So, if you look at a raw cost, you go, oh man, that part is actually more than my execution costs at least certainly in the early days, but when I look at the entire cost of what it takes to watch manage and trace a system, it's a really easy song, right? And a lot of these things don't pay off until something goes wrong. Now we're heavy users of EventBridge. EventBridge has had two incidents in USA in the last six months, right? And we were able to say through our traffic, that was going through EventBridge, that the slowdown was occurring in EventBridge. In fact, we were saying that before was alerted in the IDR VUS dashboards, to say, "Hey, EventBridge is having problems," like we watch all their alerts, but we were saying an hour before leading into Titus saying, "Hey, there's something going wrong here." Right? Because we were seeing delays in the system. So things like that give you an opportunity to adjust, right? You can't do it. You're not going to be able to get everything off of EventBridge for that period. But at least I can talk to the business and say, "Hey, we're having an impact here, and this is what's going on. We don't think it's our systems, we think it's actually something external. We can see the tries, we see it going in, we see it coming out, it's a 20 minute delay." >> There's a huge amount of value in that, sorry, Kevin, in that visibility alone, as you said, and even maybe even some cost avoidance is there, if you're seeing something going wrong, you maybe can pivot and adjust as needed. But without that visibility, you don't have that. There's a lot of potential loss. >> Yeah, and it's one of those things that doesn't pay for itself until it pays for itself, right? It's like insurance, you don't need insurance until you need insurance. These sort of things, people look at these things and go, "Ah, what am I getting it from day to day?" And day to day, I'll use Lumigo, right? When I'm developing now, Lumigo is part of my development process, in that, I use it to make sure the information is flowing in the way I expect it to, right? Which wasn't what I expected to be able to do with it, right? It wasn't even a plan or anything I intended to use it for, but day to day now, when I buy something off, one of the checks I go through when I'm debugging or when I'm looking at a problem, especially distributed problem is what went through Lumigo. What happened here, here and here, and why did that happen in response to this? So, these things are, again, it's that insurance thing, you don't need it until you need it, and when you need it, you're so glad you've got it. >> Right, exactly. >> Actually it's already said, I have a question because, yeah, I think that it's clear on that part. And how did this, if it change the developer work in Flex, do you feel different on that part? >> I think it's down to individual developers, how they use the different tools, just like individual developers use different tools. I tend to, and a couple of people that I work closely with tend to use these tools in this way, probably where the more advanced users of serverless in general inside the organization. So we were more aware of these weird little things that occur and justly double-checks you want to do. But I feel like when I don't have something like Lumigo in place, it's very hard for me to understand, did everything happen? I can write my acceptance tests, but I want to make sure that, testing is a really fun art, right? And it's picking my cabinets nice and easy, and you can run all these formulas to do things, it's just not right, and there's just too many, especially in distributed space, too many cases where things look odd, things look strange, you've got weird edge cases. We get new timeouts in Dynamo. We hit the 100,000 limit in fresh hall on Dynamo, right? In production, that was really interesting because it meant we needed to do some additional things. >> Lisa: Kevin, oh, go ahead. >> Go ahead, no, go ahead, Lisa. >> I was just going to ask you, I'd love to get your perspective. It sounds like, you look at other technologies, there's been some clear benefits and differentiators that you saw, which is why you chose Lumigo, but it also sounds like there were some things that surprised you. So in your opinion, what are some of the key differentiators of Lumigo versus its competitors? >> So I guess I've been a partner with Lumigo for like eight months now, right? Which is a long time in the history of Flex, right? 'Cause we're just out of two and a half years old. So, when I did the initial evaluation, I was looking for the things. I'm lazy, so I wanted something that I could just drop in and it would just work, right? And get the information I wanted to ask. I wanted something that was giving me information consistently. So I try to figure these things out and hit them with some load. I wanted it to have coverage of the assistance that we use. We use Dynamo a lot. We use Lambros a lot, and I want it not just cursory coverage, how it's just another one of the 20,000 things that they do, I wanted something that was dedicated to it. That gave me information that was useful for me. And really the specialist serverless providers were the obvious choice there. When you looked at the more general providers, the Datadogs and New Relics, I think if you're in an environment that has a lot of other different types of systems running on, then maybe the specificity that you'd lose is worthwhile, right? There's trade off you can make, but we're in a highly serverless environment, so one of the specificity. When I looked at the vendors, Lumigo was the one that worked best straight out of the box for me, it gave me the information I wanted. It gave me the experience I wanted, and to be frank, they've reached out really quickly and had a chat about what were my specific problems, what I was thinking. And all of those things add up, a proactive vendor, just doing the things you wanted to do, and what became and has become a lasting partnership, and I don't say partnership lightly 'cause we've worked with a number of other vendors, right? For different things. But Lumigo, I have turned to these guys, 'cause these guys know serverless, right? So I've turned to these guys when I've gone, "Look, I am not sure what the best approach here is." You have trusted me about it, this is vendor, right? >> Right, but it sounds like it's very synergistic, collaborative trusted relationship. And to your point, not using the term partner lightly, I think arises, probably couldn't have been a better testimonial for Lumigo, its capabilities, and what you guys are able to do. So I'll give you, Erez the last word, just give the audience a little bit of an overview of the AWS partnership. >> Sure, so AWS has been a very strategic partner for Lumigo, and that means that, I would say the most critical part is a product, is a technology. And we are design partners with the serverless team. And that means that we work with AWS to make sure that before new services are released, they get our feedback on whether we can integrate easily or not, and making sure that on the launch date, we are able to be a launch partner for a lot of their services. And this strong partnership with R&D team is what's allowing Lumigo to support new services out of the box like Kevin mentioned. >> Excellent, gentlemen, thank you so much for joining me today, talking about, not just about Lumigo, but getting this great perspective of it through the CTO lens with Kevin, we appreciate your insights, your time, and what a great testimonial. >> Thank you very much, thank you, Kevin. >> Thanks, Lisa, thanks Erez. >> You're most welcome. For Erez Berkner and Kevin O'Neill, I'm Lisa Martin, you're watching the AWS Startup Showcase for Q3. (gentle music)

>> From theCube Studios in Palo Alto in Boston, bringing you data driven insights from theCube and ETR, this is breaking analysis with Dave Vellante. >> As we reported in our last episode tech spending overall continues to be significantly muted relative to 2019. Now, our forecast continues to project a 4 to 5% decline in 2020 spending, and a tepid 2% increase in 2021. This is based on the latest data from ETR surveys of CIOs and other it buyers. Nonetheless, there continues to be some sectors and vendor bright spots in what is generally an overall challenging market. Hello everyone, and welcome to this week's Wikibon Cube Insights powered by ETR. My name is Dave Vellante, and in this breaking analysis, we welcome back Erik Bradley from ETR to provide added color from my solo flight from last time. Erik always a pleasure to see you, thanks so much for coming back in theCube. >> I always enjoy it. Happy Friday Dave, We're almost through. >> Happy Friday. They just blend together. Guys, if you would bring up the first slide, I just want to summarize the situation. This is from ETR's latest findings, I just extracted some. And I want to go down very quickly, Erik, and then get your take. As I said, technology buyers expect the downturn for 2020, but this quarter, coming into fourth quarter, minus 3.2% was ETR's forecast, that's year to year spending decline and a 2% uptick in 2021. Now, Erik this is slightly, what I call it slightly less bad, relative to last quarter. So sequentially it's less bad. >> Yeah, there's a couple of things to break down there. So first to begin with, beginning of the year, when we launched not only our spending attention surveys, we did a simultaneous COVID impact survey, and that's where we caught originally a 5% decline was expected. So although negative 3.2 was probably the worst quarter over quarter lapse we've seen, as a matter of fact it is the lowest drop we've had theory, going into 2021, the IT people that we've actually surveyed are actually expecting a 2% increase. So there is a reason for optimism, but if we're looking at the current data set, there is no doubt the picture remains a little bit bleak. We can go into different sectors and vendors where they are impacted, but I think maybe if you're willing, I think it might be worth just sort of breaking down the demographics of the survey a little bit and how we got to that 3.2% survey over survey decline. >> Yeah, and we have a chart on that. But before we get that, I just wanted to lay out some of the other key points of your analysis. The other one, which is we talked about this in the last episode, we call it a slow thawing. Hiring an IT project freezes are thawing, with fewer companies expecting layoffs. So that gives us some bright spots, but there are definitely a widening bifurcation between vendors gaining share and those who are donating share. And then, you know, again, relative to last quarter survey we're seeing government and education and fortune 100, you guys are showing the deepest cuts from the last survey. Where's IT Telco, retail and retail consumer are showing a little bit more stability. And then of course you talked about the work from home which we've covered doubling from pre pandemic. Pretty interesting findings from your COVID survey. >> Yeah, it's a fantastic, and this is the fourth iteration of this survey that we've done now. So we've been able to track it very quickly, launched it in the field when we realized the true impact of what was happening in early March. This is our fourth version, and we've been able to track it overall. Yes, without a doubt government, education are being the biggest impact, the biggest declines without a doubt. Now, clearly the caveat to that is if there's any sort of government policy maybe those could actually help a little bit, but for right now, those are getting hit the most. Retail consumer is fairing much, much better, and the IT companies, as generally, we're seeing in the market as well, they can, you know, are still spending money and still moving. But the reason for optimism actually comes from multiple metrics. And I will say, we have caught a bottom on all of the negative metrics at this point. Now, who knows what will happen the next time we do it, right? The world is always fluid. But based on this, this is our fourth iteration of this survey, whether it be IT projects being frozen, whether it be layoffs, whether it be just overall expected budget increase, everything looks like it is already bottomed and there is some optimism going into 2021. Of course, the January survey that we launched will be able to corroborate that hopefully, and we'll have much more granularity into those findings at that time. >> Great. Okay, now let's get into the demographics that you referenced for. This next slide shows those. The record number of respondents Erik, congratulations on that. And so take us through the makeup of the survey respondents guys, if you bring up this next slide. >> Yeah. So for the October 20, what we're really doing here is we're asking the it decision makers to update the survey responses they gave us in July. We're basically saying, okay, you thought you were going to spend this in the back half, what did you actually do? And in this particular survey we had 1,438 qualified IT decision makers get involved. That's 60% of the fortune 100 is represented, almost a quarter of the global 1000, and we had about 35% of the fortune 500. The industry breakdown is all across the board, whether it's financials/insurance, IT/Telco, we have industrials/manufacturing, we have energy/utilities, we have government. So it's really a great cross section. Now, geographically, that tends to be about 80% North America. We are heavily concentrated in that area, but we also have a 12% EMEA, 5% APAC and remainder is Latin AmErika. If there were any visibility concerns at all would probably be in China. It's just not that easy to get qualified IT decision makers from China to respond to us. But that's an area we are working on going forward, but overall a huge survey response, certainly meaningful end, and we're very happy with the data that we collected this time. >> Okay, thank you for that. Now, I want to go into the next graphic here, and I want to look at how net score has changed over time. And I want to remind people that, so this slide basically goes back to 2016, and shows some ebbs and flows and then some real strength coming in, 'cause you see 17 and 18, and you may forget going into Q4'19 and into 2020, the ETR data was telling us, hey, things are going to slow down a little bit. It's hard to remember that. And so, and the thinking back then was okay, last couple of years, people have spent a lot on digital transformation, and would a lot of experimentation, they were hanging on to their legacy stuff, and with all that technical debt and they were experimenting with a lot of the new technologies. And what we saw coming into Q4 2019 was people beginning to unplug some of that and making bets basically, unplugging some of the legacy stuff. Oh, and by the way, maybe saying hey, the new stuff that we tried didn't work, we're going to do less experimentation. So we saw a somewhat depressed next score, and you can see that in here coming into 2020, and then of course COVID hit and you can see the bottom fell out. But wow what a drop, I mean, that says it all, a lot different than what we're seeing in the stock market. >> Yeah, first of all, just a great recap on what we caught last year. Really well done. So at that time there was concurrent spending. There was a lot of proof of concepts being done. People weren't exactly sure how to transition off, how fast they were going to get into the cloud, how fast they could make that digital transformation. And they were kicking the tires on everything, and there was a ton of spend. It was the golden era of IT spending at the time. But we did catch that some of that was coming down. So what we will see now is obviously that spending was going to cool off either way, but now with the global pandemic impact hitting what we've caught, of course, is the biggest survey over survey decline. 3.2% was matched at one other point in our survey's history, but that was at very elevated spendings, so that drop was not as meaningful. When we're seeing from a more baseline that drop right now is extremely seasonal, and extremely meaningful, my apologies. Now, I do want to make a quick caveat that usually the October survey catches some seasonality, because a lot of people have expected spend in the back half that doesn't always materialize. But make no mistake, this is way beyond our normal seasonality. This trough is a real metric. >> Yeah, and when I talk to buyers and I talk to even salespeople, for if you want the truth, you'll talk to salespeople, if you can get the truth out of them, which you usually can. Sales and engineering, that's really if we want to know what's happening in companies, but they will tell you that their visibility, same with the buyers, they're saying, look, I think I'm going to spend and I think I'm going to get approval on it, but the normal buying signals, you kind of have to take with a grain of salt because it's, the buyers don't know the sellers don't really know. I mean, they think they've got reasonable visibility but things change so fast as we know. So you have to be really, really careful. All right, let's drill in to some of the sectors, and that's really the next two slides, guys, if you bring up the first of the next two. So this shows the change from July to October. So the last survey to this survey, 2020, and the green bars of July, yellow bars are October. And you can see right away, jumps out at you, container orchestration and ML and AI, and we've got some other data on this jump right off the charts. They're still elevated levels, so that's a real positive. You can see AI actually, maybe waning a bit, and I think that's probably, Erik, is a lot of it is just, you don't even see it, it's just embedded. But take us through this first chart and then we'll dig into some of these sectors. What are you seeing? >> Yeah, certainly. So from a sector breakdown point of view, that lesson, none of them were spared, let's be honest, right? There's a slow down in spending. But containers and containerization were by far the most stable. So clearly this is a priority. People are recognizing that they need to go that route. Nobody wants to be tied to any particular cloud provider. So container and containers are moving the best, they are looking about as stable as they can be. When we drill down a little bit further in there, we're seeing Kubernetes of course, Microsoft and AWS really supporting in that sector. Now, when you talk about the ones that had the biggest survey over survey declines, we are looking at ML/AI, but like you said, still elevated spend. So even though there was a big survey over survey decline, the overall spending intentions are healthy. Nobody is getting away from it. Also to corroborate that in the COVID impact study, we asked people, given the current situation where their priorities are, and unfortunately in that area ML/AI and the RPA we're actually not positioned as well. So it actually corroborates the COVID impact survey, corroborates what we're seeing here in our larger intentions. Now, when you look at ML/AI, Microsoft is still very well suited in that area. Virtualization was another big area that dropped, which was interesting because I think the immediate COVID impact and the work from home, we saw a little spike there. I think we definitely saw companies like Citrix, right? F5 and Nutanix and AWS workspaces. They all had a really good impact, positive, when we first hit, but virtualization is dropping quite a bit there. And again, no surprise, Microsoft is well positioned as well. And then lastly, enterprise content management also had a big, big drop-off, and there you're looking at Adobe Box, Open Text, those are the type of companies that seem to be having the biggest survey over survey decline and ECM. >> Yeah. And I just want to make a comment on this first of the two slides. Is you see security, it's okay, there's a little bit of decline, but there's the story of the haves and the have nots. If you're an end point security, you're in cloud security, you're in identity access management, there's some real tailwinds for you right now. You're seeing that with Octa, CrowdStrike and Zscaler, SailPoint, you know, had a really good quarter. So that's the story of kind of the, a mixed bag. If you go to the next slide, guys, what jumps out here on the second sector breakdown, and Erik you alluded to this as RPA, very elevated, although down, somewhat still, again, very elevated and cloud computing. I mean, that's all everybody wants to talk about. This is a large market that continues to grow very, very fast. >> Yeah. It's a A2 cloud, right? I mean, even the cloud, we're kind of shocked and we saw that too. But, you know, again, it's still a healthy survey at 4Cloud. Spending is still there, but what we are seeing is a pretty big survey over-serving decline that is probably, if you had to translate that, it's going to show slower growth. Still double digit growth, but slower than we expected. And interestingly in the cloud, again, Microsoft is very steady, GCP steady. We saw AWS soften a little bit, and that's something that I think we need to keep an eye on there, we are seeing some softening trends. IBM and Oracle, unfortunately, no matter how hard they push, it doesn't really seem to be making a dent, at least with our it decision makers that respond to the survey. But one thing that was interesting was VMware on AWS actually looked much, much better than VMware alone. So on the cloud side, those are pretty interesting takeaways. >> Yeah, we talked about that a couple of episodes back as the, well, couple of things to pick up on your comments. You mentioned IBM and Oracle, they're just so large, they're growing businesses are not growing fast enough and they're not large enough to offset the decline and their declining businesses. Yet they're huge, they have, they throw off a lot of cash and so maybe their stock's not going through the roof, but they're pretty stable companies from that regard. I wonder, maybe AWS is starting to hit some of those, the law of large numbers. I mean, it's still growing very, very rapidly for a 45 plus billion dollar organization, still growing well into the double digits, so it just gets harder. And then, but the other thing I wanted to pick up on is you mentioned VMware cloud on AWS, we're seeing those hybrid solutions really start to pick up the multi-cloud solutions, which I was a real skeptic a couple of years ago 'cause it wasn't really real, now becoming real. And I think when you talk to, you know this well from your Ven discussions, people are looking at options for cloud. They want multiple clouds, the right horse for the right course, they want to reduce their risk, they want to ensure exit strategies and some clouds are just better at some things than others. >> Yeah, completely agree. And as you know, I do interview a lot of these IT decision makers that we survey to get a little more granularity and to dig into the details, and you and I just, great example. We did a session on Data Warehousing as a Service, we're at Snowflake. And the main reason that people love them is 'cause they have cloud portability. They can move across multiple clouds. Nobody wants to be tied to one cloud provider, they need to be agnostic. And if you look at, you know, something like Microsoft, right? Their Software Suite is fantastic. So most people are going to be aligned for them. They provide great active directory, the enterprise applications are absolutely incredible. But if you're looking to do straight ML/AI or straight data warehousing, maybe AWS Redshift, maybe Google Big Query might be a better fit for you. There's no reason to be tied into one. So what we're seeing more and more is those vendors that offer cloud portability or hybrid availability to do some on-prem for security, some cloud, they're really taking a step up in our recent surveys. Another comment you made Dave, if I can just backtrack to it is, you kind of mentioned how some of the vendors are taking more and more share. We are continuing to see this theme of a widening bifurcation, where although the overall spend that pie is shrinking, the leading vendors are taking much bigger slices from that pie. And that is continuing across the entire year. >> Yeah, definitely a time of disruption. So thank you for bringing that up. Okay, the next graphic I want to show you is actually a motion graphic, and what we're showing here is one of our favorite views. On the vertical axis you've got net score, remember, net score, essentially ETR, every quarter like clockwork asks customers are you spending more you're spending less, it's more granular than that, but essentially they subtract the red from the green and that leaves you with net score. So the higher the net score the better on the vertical axis, on the on the horizontal is axis is market share, its presence, its pervasiveness in the dataset. So you want to be up into the right, of course, like all these charts and XY's. And what we're showing here is, we go back to October, 2018. Remember this is the October survey and you can see the movement and what's happening. And a couple of points here really is one is container orchestration and container platforms, cloud, RPA, ML, they all stand out. And now we, you can see the the context of their "market share" as well, and you see that bunching, you see some of the Legacy stuff, the more mature markets like storage and PC tablets and laptops. They don't have a huge next or outsourcing, not a big net score, but they're there and they're kind of bunched up, down in the middle. But you can also see how they've slowly got depressed over time, even the elevated ones. Nobody in the recent survey is over a 60% net net score. I think you guys said that the overall net score was the lowest in history. So this is just a good way to visualize the various sectors and how spending, momentum and share is shifting. >> Yeah, that's a very good point, and you are right. The overall survey net score is actually 25.3% and it is the lowest ever we've captured. So that actually is translating into what we expect to be single digit declines in overall growth in IT budgets, which again is in line with what we've been saying. We caught early on about negative 5 1/2, that is improved now it's in this quarter to about negative 3 1/2, but if you look at the mid point here, we're very clearly in mid single digit declines, and the entire area is being impacted. Now, there are certainly some areas that are more important than others, there's no doubt about it. But yeah, outsourcing is one you mentioned, absolutely getting decimated. Nobody really has the money right now to be doing IT outsourcing, that's just not a priority. The priority is remote connectivity, remote security, how do I get identity access and governance to make sure that my employees are doing what they're supposed to be doing, even though they're not on my network anymore. All of those things are continuing. And as you saw on the COVID-19 Impact Survey, they're not going away. You had mentioned on a solo session you did, I think a week ago, where you have cited our data saying that permanent workforce is going to double from where it was in pre-pandemic levels. So that means a lot of the people that slapped a bandaid on their networking to get their employees to work from home, that bandaid solution is not going to work. They need to find one that's permanent now. So the areas of spend, although it is declining, there are very clear delineations of where that spend is going. >> Yeah, I want to just pick up on something you said about the work from home doubling, 'cause I've shared that data with some folks and had some discussions. We're talking about people that work from home, not come in a couple of times a week, this is the work from home component. And so I think the hybrid is going to increase as well, but the hardcore work from home, I think it was mid-teens, 16% or something doubling in the post pandemic was the expectation. And again, I just wanted to sort of clarify that I think your data there is quite good. How about some of the vendors? I think, now that's Snowflakes public, you guys may be doing some forecasts there. Let's start there. >> Sure, yeah. So it's fun to talk about the high level, right? And talk about the sector breakdown and where we're seeing things, but at the end of the day, people just love to talk about the individual vendors. So there's a few things that were interesting, yeah. We were able to finally come out with a real viewpoint on Snowflake now that they're out in public, and we kind of launched with a positive to neutral viewpoint. I don't think there's going to be anything here that shocks you. We're absolutely outstanding expansion rates. All the commentary we get from our CIOs are just incredible, the market share gains are about as high as you're going to see in the survey, they are extremely well positioned to continue executing, and this is not in the data set, but we also know that that management team is fantastic. I would think that they had set themselves up coming out as a public company not to completely disappoint. And everything in our data set shows absolutely no reason why they would disappoint. >> Well, and so you may be wondering folks, like, well, wait a minute, with all that great news, I mean, how could they be positive to neutral. Maybe it maybe neutral, the reason is because they have a 66, roughly $66 billion valuation. And what ETR is doing is they're taking that into consideration as well relative to, so they're looking at the street forecast, the consensus forecast and saying, okay, how does the data line up to that? And so a lot of people are asking the question, can Snowflake live up to its valuation. I don't think there's any lack of total available market here. I mean, it's very, very large, the data market, it's enormous. And as, just a plug for an event that we're doing on November 17th, it starts, we're doing a global event, and we're going to be looking at this issue very closely, interviewing customers and partners and executives and, you know, you can judge for yourself if you think the vision, they're putting out this vision of a data cloud. You see this, if this vision, you think is going to have a big enough term that they can grow into, and as Erik said, great management team, will they be able to execute? Decide for yourself, but very exciting IPO obviously that we've tracked quite closely. Elastic is another one that you guys have followed quite closely. I know you've got some data there that you want to share as well. >> Yeah, I certainly do. The APM spaces is really interesting. One last quick point on Snowflake. We don't have regression forecasts on them, because they haven't been out public long enough for us to be able to do that sort of back-testing. So without that data science behind us, we will never really go with a full positive. So to your point that saying positive to neutral is not negative or neutral stance whatsoever, it's just without that regression support behind our data, that's what we just tend to do. Because at the end of the day, we're a data science company, so.. >> Yeah. You need some some history there to really make those calls. But yeah, let's talk about Elastic. >> Yeah, sure, you got it. So recently I hosted a panel on the APM and monitoring space. It was incredibly enlightening. It's a very crowded space that our CIOs told us is right for disruption. And it ended up being a little bit of an avalanche in our data, because it wasn't just Elastic, but it was also Splunk and Dynatrace that we ended up putting ratings on. Now, Elastic as we know is an open source model, a freemium to pay type of model. And we normally try to stay away from open source models, 'cause it's kind of hard to predict how that converts to revenue, but the data was so strong that again, we came out with a positive to neutral rating on Elastic. It was based on just elevated spend levels across, there was almost no negativity, we weren't seeing any decrease or replacement indications, really solid positioning in the fortune 500 accounts, which I was a bit surprised about. And the other thing here is that Elastic tends to be really expanding in the information security. This is no longer just about monitoring and logging, they are becoming a very relevant infosec play and they are breathing down the necks of Splunk. They can do the same thing and they can do it much cheaper. The caveat being, you need to have the IT and the human skillset to run Elastic. So it really comes down to, are you sophisticated enough with the human capital management to run it? But everything we saw here just incredibly improved competitive positioning, they actually had the number one net score in all of information security in any vendor that had over 50 citations. It was just too hard to ignore, we had to come out with a positive neutral. >> That's super interesting Erik, and of course, yeah, we covered that space recently. Everybody wants a piece of Splunk and have for a number of years, but, you know, you see in Datadog come after it, then you see some startups getting into the space. Jeremy Burton launched his company, Observe, Honeycomb is in that, they kind of coined the term observability. Kakao Search is another one. Ed Wall's joined that company, and so you see a lot of folks really going after that space, why not? I mean, it's such a successful company. The pickup of SignalFX filling some holes, we talked about that on the Ven, and it's a very interesting space, and one I think has some somewhat depressed levels from a net score standpoint but as some of your Ven observers said, this market is here to stay and it becoming much more important as part of digital transformation, as part of a dashboard of digital transformation. >> Yeah. Coining that term observability really just hit it on the nail on the head. When we just talked about monitoring an application, that's not what it's about anymore, right? You need to have observability in multi hybrid cloud environments, whether it's your infrastructure or people actually writing code for your application. And so that single pane of glass, end-to-end is the holy grail of monitoring, and that's what these guys are pushing for. The New Relics, the Datadog's, the Elastics, they're getting there more quickly than Splunk and Dynatrace or AppDynamics from Cisco are. That's what the people are telling us, the ones I speak to, the CIOs that use it in the field. They're getting there more quickly and they're doing it more cheaply. Now, this is not to say Splunk is not a great company, we know it is. And also Splunk has more API integration into any ecosystem you want. They're not getting pulled or ripped out anytime soon, we're not saying that. But when we look at our data, we had no choice but to come out with a neutral to negative. They are deteriorating and their spending intentions, their customer growth is completely stalling, we're not seeing any more increased perversion in our dataset or among customers. There just wasn't really anything we could really do. Looking at the data set and that's what we do, we had no choice. There's a lot of skepticism heading into the back half of this year and next year, there's so much competition coming after them, and some of these people are just giving it away for free. It's pretty hard to compete with free. >> Yeah, free is very powerful. All right, speaking of skepticism, Rackspace had their IPO, what do you see in there? >> Oh man, I'm not really sure how to start there. But listen, I don't want to beat a company while it's down, but their net scores are actually negative. I think at the negative 20% range, if I could possibly recall that. But listen, Rackspace, when they were private, let's give them some credit, right? They decided to go out and buy a bunch of different managed service providers, they tried to align themselves with AWS, with Oracle. So they've got this whole bundle thing right now that isn't just straight cloud computing anymore. We'll see if that plays out. But clearly we saw that the IPO was not a very special IPO. In this environment the valuations in the technology stocks being very elevated, having a negative IPO was very telling. But sticking straight to the data, basically we're seeing negativity across several years, it's the worst position vendor in cloud computing that we even cover. We just had to take a look at it right now, and just be honest and say according to the data, this is a very negative data set, there just isn't much we can do about it. Wish them the best, I hope their MSP revenue starts kicking in, and hopefully it'll change. But for right now the snapshot of our data was quite dire. >> Okay, Erik, Well, thanks so much. So let's update folks, so the ETR is exiting, it's quiet, period, which I love, because that means I can have the data and share with you. So we'll be updating our cloud scenarios, security, automation, our infrastructure, and many other segments as well. Certainly the data piece, we've been tracking snowflake very closely. And of course, Erik, you guys are already gearing up for your January survey. So, you know... >> It never ends Dave. And I've... >> Well, I got a really... I've got a sizzle panel that I'm doing next week as well, where we got four sizzles talking about security threats and priorities for 2021. So as soon as I wrap that, you'll be the first one I get my summary to. >> Oh, those are great. I mean, there's such deep dives with practitioners, and it's just an open discussion. So Erik Bradley, thanks so much for coming back in theCube. >> Have a great weekend Dave. >> Yeah, you too. And thank you for watching everybody this episode of Cube Insights powered by ETR. Go to etr.plus, that's where all the survey action is. I publish every week on wikibon.com and siliconangle.com. All these episodes are available on podcast. Wherever you watch, you can DM me, I'm @DVelllante. I post on LinkedIn, you can comment there or email me @david.vellanteat, @siliconangle.com. This is Dave Vellante for Erik Bradley. Thanks for watching everybody, we'll see you next time. (upbeat music)

(upbeat music) [Narrator] - From New York City, it's theCUBE. Covering New Relic Futurestack 2019. Brought to you by New Relic. >> Hi, I'm Stu Miniman and the theCUBE's exclusive coverage of New Relic Futurestack 2019. We're here at the Grand Hyatt which is right next to Grand Central Station in beautiful Manhattan, New York City. We're going to be speaking to a number of customers as well as the executives. It's the seventh year of the show, our first year here and helping me kick off the event, always happy to have a customer on. Dirkie Gertenbach, who's the global B2B engineering lead at AB InBev, a local customer here. Dirkie, thank you so much for joining us. >> Thanks, nice to be here. >> Alright, so, nothing better than getting together with a bunch of your peers you know, downtown New York City, talk about, you know, some cool technology. Before we get into the tech though, I think most people understand AB InBev you know, global beverage brand, really well-known, I know I saw beer trucks when I was making my way through New York City. But tell us a little bit about, kind of, the company and your role inside it. >> Yeah, sure. So, yeah, we're a global beer company, we sell beer. My main focus is the engineering lead at InBev and we look specifically at the e-commerce side of it. So, the digital sales. We've been going through a large transformation these last couple of years, where we flew from more traditional sales to like, digital sales, and we've been implementing our e-commerce platform in a couple of countries the last couple of years. >> So, transformation, it's not just that AB InBev goes from a couple of the largest known brands, you know, in the beverage to "oh boy, now there's so many different micro beers and and different things, I know I can't keep up with all the locals", but even a large brewery like your company - has all little brands, a similar thing I guess is happening on the technology side. >> Yeah. >> Yeah, maybe, tell us a little bit about you know, what that transformation, you know, what's causing that transformation and what is happening inside your or, to support this transformation? >> Yeah sure. So when we started off the digital transformation obviously, it was much simpler. We had a couple of applications in only one or two countries. And in these last two years we've been expanding and we've been implementing it in other countries and we've started moving from a monolithic to a more micro service central so obviously it's like not only one application now, it's like, it's hundreds of applications. In the beginning, it was quite tough because we were moving, we were developing stuff much more quicker than what we could support and that's when we started talking to New Relic. And we looked at their product and looking at a couple of ways of streamlining this operational and having more of a a stability on our products overall. Like, there's still have a lot, we are still immature in a lot of spaces. >> Yeah, so bring us in. You talked about you applications. You know, so many customers are going from their monolist to their micro services but they usually have, you know, that transition is not something that's done overnight, and they need to be able to manage all of that environment. Give us a little bit of view into, you know, what you can about your application portfolio, where you are on that journey and then, you know, what tool sets are you using to be able to manage, monitor and you know, the word of the day of course is observability, so you know, what that means to you and your-- >> Yeah sure, so like I said we've (mumbles) into micro services which is (mumbles) There's a lot of different applications that's running and the main thing that it showed is just having visibility on infrastructure as well as application performance. And application where it's optimal or not. So those are the most basic. We got New Relic involved and that's one of the main tools that we use for observability today. We were using a couple more but we are, like, putting everything into one bucket now. So, it's interesting, the new stuff. What they announced today, that's one of the stuff that we've been missing that's really going to help us. Especially the data base monitoring and the network monitoring. That's something to all our stuff is on Azure so we rely a lot on Azure monitoring. But it doesn't always give you that granularity of like, observability. One of the other things that we are excited about is the, what's the other thing? Sorry, I forgot, I'll come back to you. >> That's all right. So first of all, you know, are you using New Relic One from New Relic? >> We're starting to use it now, so we still use-- >> So walk us through a little bit the journey with New Relic. What products were you using? And tell us where you are with the platform and what you think of the vision of, as Lou said, it's a capital P platform in certain characteristics, that New Relic built when they had in mind? >> Okay, yeah, sure. So in the beginning we were using the browser and Sonetics just like a normal looking whether that website is up or down, and then we started looking so we've got ABM running on every single server we've got now, that gives us like a lot of visibility and we use the insights a lot, so just dashboards. What we found in the new One platform is the dashboard so we can create the linear of data and the visibility that we can give to our stakeholders. It's much better. Just the visibility on the different. I can give you a couple of used cases that we've gone through in these last couple of weeks. So for example, on one of our applications we're having like, login failure, a lot of login failures. And we are really struggling to look at locks and stuff and just pinpointing with that. So on all the data that's coming into New Relic, we started creating dashboards where we can actually see what's the different causes of these login failures and we can actually pinpoint where do we need to put our focus? So it was a good example. And then the other nice thing that I like about the one that we are using actively is the Kubernetes monitoring. It gives you visibility of your entire cluster every single product that's on there and you can just quickly see if there's a part that's struggling or not. >> All right. If you can, I was wondering if you could bring us inside your Kubernetes? How long have you been using it? Do you build your own or using one of the cloud or some other solutions? Tell us a little bit about your stack. What that solution, and where New Relic fits into it? >> Yeah, we started off the Kubernetes just over a year ago. We're using Azure AKAs. So all our stuff is in Azure. And so yeah, in the beginning, we built all of the applications and everything ourselves, so it's all out set. And again, just coming back to monitoring within Kubernetes, it's all controlled. Like (murmurs) It's difficult to have clear visibility so yeah, when they brought out the Kubernetes like monitoring that was like a life changer for us. It's just operations, we're being much more productive now in terms of if we need to scale up and whether our reports are healthy or not that definitely helps a lot. And I think that we've been working (mumbles) It's just the DevOps, we're very new in DevOps, and just the visibility that New Relic gives us helps us a lot in like, pinpointing where we need to focus our DevOps effort. So that's also a good help. >> Stu: Okay. You'd mentioned that there was some things announced that had you excited, things that you'd been looking for. Maybe you can explain, you know, which items jumped off the board at you this morning. >> Yeah, so again, just the database monitoring and the network traffic. That's very important. And then the one thing that's, we were just busy investigating a lock analyser. And the lock ingestion that they announced today that's very exciting. So I mean, we're already in New Relic so I think we're definitely going to look at that. That's going to be a big help. And then it just brings all our data together. And after you've used different tools for locks and monitoring, that's something that makes me very excited. And the other thing is, we're also use SAP in (murmers) and the partnership that New Relic is staring with SAP now, that's also very exciting. Something I'm seeing forward to. >> Stu: Okay. Was there anything you were hoping for that you haven't seen yet? Or anything on your wishlist that you want from either New Relic or from Azure, or from the industry as a whole? >> Nothing yet. I mean, like I said, we're still at early stages. I think maybe in the next year or so we're probably going to start saying, "Hey guys, maybe you need to build this as well" but for now it's just like they keep delivering stuff that before we can even think about it. So that's great. >> Uh, Dirkie, it's your first year coming to Futurestack. What specifically bought you hear? What are you hoping to get our of the day? >> Yeah, it's my first time here. Hopefully I'll come, like I said, I've only got a couple of hours today but I think just in terms of seeing the new stuff that can help us in our operations, our business operations and as well as Stave Apps, it's exciting to see how this can transform our business going forward. In terms of what else I want to see, I don't have high expectations at this stage. Like I said again, they keep delivering before we can actually say what we want so that's just great. >> You mentioned that you're early in your DevOps journey inside the company. Any other color you want to share about, just kind of organizationally what's changing in your business? You know, there's so many new things coming on. You know, you've watched Kubernete's a year ago, you're getting into logging, so the roles and responsibilities that your team members have, and keeping up with all of these various technologies, how's that impacting the work force and the jobs that they do? >> Yeah that's great. So again on our services that we've got we've got a lot of new teams as well, and we've been in a kind of a hyper growth stage, and we're building a lot of micro servers and stuff. We struggle to know whether the performance of that micro service is good enough or not. So that's one thing that our developers struggle with and that's something that New Relics has helped us with. Every single service that we've built, we put it on New Relic, and we've got a, like, you can see three days ago what has been average performance of this API. And that helps us also to type back to (murmurs). So we've got this arranged with each of our services, for our API inpoints , and this gives us a easy way to see whether we're on track or not, and it then translates back to the developer on whether they need to do something to increase that. Another great thing that we've been doing with New Relic with the VP of engineering is they've been helping us a lot in setting up our sites reliability teams. So we've had a couple of discussions with them these last couple of weeks and they've helped us a lot in just identifying what's the different teams that we need to bring to our organization to keep operating in this way and the growth that we are. Also something that's great that we've been looking at, and New Relic has also helped us a lot there, we had a lot of monitoring, we're monitoring everything, but the data doesn't, we don't make a lot of use with the data. So what we've started doing now is to say, "Okay, what's the most (murmurs) path on our application?" "What is it the customer needs to do?" "What's the journey he needs to go to get his (murmurs)" And that's our most critical. So then we went and we worked with New Relic to say that, "Okay guys." "so help us map this to what's the infrastructure." "What's the application that needs to be up to support this journey?" and we created thresholds on that, and alerting. We're almost at a place now where we've got all the stuff mapped and alerted, and proper actions on that, which is also great. It's helping us to be more pro-active and we rely less and less on our customers to tell us, "Hey, there's a problem on the application." >> Stu: Alright. Lou was talking about all the applications that can be built on top of this platform. I saw the network flows, do we think we're going to see the beer flows by the time we come back a year from now? >> The network flows is great. So I need to do a little bit more deep dive onto the application build, but I can start thinking of a couple of examples where we can really use that to deep a little bit deeper into what the data that we've got day to day. So yeah, that's also exciting in the future. >> Well Dirkie Gertenbach, thank you so much for sharing what your groups going through at InBev. Thanks so much for joining us. >> Great. Thank you Stu. >> Alright, and lot's more coverage here at New Relic, Futurestack, in New York city. I'm Stu Miniman and thanks for watching theCUBE.