 Hello friends, welcome back to theCUBE's live coverage of AWS re-invent 2022 from the Venetian Expo in Vegas, baby. This show is absolutely packed. Lisa Martin with Dave Vellante, Dave, this is day two. We're really full day one of our wall-to-wall coverage on theCUBE. We've had great conversations the last half day this morning already. We've been talking with a lot of companies, a lot of Amazonians and some Amazonians that have left and gone on to interesting more things which is what we're going to talk about next. Well, I'm excited about this segment because it's a really interesting space. It's, you've got a search company who's gotten into observability and security and through our ETR partner, our research, we do quarterly research in Elastic off the charts. Obviously, they're the public companies so you can see how well they're doing but the spending momentum on this platform is very, very strong and it has been consistently for quite some time so really excited to learn more. The voice of the customer speaking madly from Elastic, its chief product officer joins us, Ken Exner. Ken, welcome to the program. I thank you. Good to be here. So a lot of us know about Elastic from Elastic Search but it's so much more than that these days. Talk about Elastic, what's going on now. What's the current product strategy? What's your vision? Yeah. So people know Elastic from the ElkStack. Elastic Search, LogStatch, Kibana, very, very popular open source projects. They've been used by millions of developers for years and years but one of the things that we started noticing over the years is that people were using it for all kinds of different use cases beyond just traditional search. So people started using Elastic Search to search through operational data, search through log, search through all kinds of other types of data just to find different answers. And what we started realizing is that customers were taking us into different spaces. They took us into log analytics. They started building log management solutions and we said, cool, like we can actually help these customers by providing solutions that already do this for them. So that they took us into observability, they took us into security and we started building solutions for security and observability based on what customers were starting to do with the platform. So customers can still use the platform for any number of different use cases for how do you get answers out of data or they can use our pre-built package solutions for observability and security. So you were a long time Amazonian. I was, I was. Talk a little bit about some of the things that you did there and what attracted you to Elastic? What was, because it was only been a couple of months, right? I've been here three months. I think three months as of yesterday. And I was at AWS for 16 years. So I was there a long, long time. I was there pretty much from the beginning. I was hired as one of the first product managers in AWS, Adam Salipski hired me. And it was a great run. I had a ton of fun, I learned a lot. But after 16 years, I was kind of itching to do something new and it was going to take something special because I had a great gig and enjoyed the team at AWS. But I saw an Elastic sort of a great foundational technology that had a lot of momentum, a huge community behind it. I saw the business opportunity of where they were going. I saw the business opportunity of observability and security. Like these are massive industries with tons of business problems. Customers are excited about trying to get more answers out of data about their operational environment. And I saw that customers were struggling with their operating environments and things were becoming increasingly complicated. Now we used to talk in AWS about how customers want to move from monolithic applications to monoliths. But one of the secrets was that things were increasingly complicated. Suddenly people had all these different microservices. They had all these different managed services and their operating environment got complicated. Became this constellation of different systems all emitting data. So companies like Elastic were helping people find answers in that data. Find the problems with their systems. So helping tame that complexity. So I saw that opportunity and I said, I want to jump on that. Great foundational technology, good community and building solutions that actually helped solve real problems. So before you joined you probably looked back and said let me think about the market, what's happening in the market space. What were the big trends that you saw that sort of informed your decision? Well, just sort of the mountain of data that was sort of emerging. Adam Silitski and he has talked this morning. He began by talking about how data is just multiplying constant. And I saw this. I saw how much data was businesses were drowning operational data, security data. Now if you're trying to secure your business, you have all these different end points. You have all these different devices. You have different systems that you need to monitor. All tons of data. And companies like Elastic were helping companies sort of manage that complexity, helping them find answers in that. So when you're trying to track intruders or trying to track malicious activity, there's a ton of different systems you need to pay attention to. And there's a bunch of data. It's different devices, laptops and phone devices and stuff that you need to pay attention to. And you find correlations across that to figure out what is going on in your network. What is going on in your business? And that was exciting to me. This is a company sort of tackling one of the hardest problems, which is helping you understand your operating environment, helping you understand and secure your business. So everybody's getting into observability. Right, it's a very crowded space right now. First of all, it's like overnight it just became the hottest thing going. VCs were throwing money at it. Why was that? And how are you guys different? Well, we began by focusing on log analytics because that was the core of what we were doing. But customers started using it beyond log analytics and started using it for APM and started using it for performance data. And what we realized is that we could do all this for customers. So we ended up sort of overnight, over a course of three years, building out a complete observability suite. So you can do APM, you can do profiling, you can do tracing, sort of distributed tracing, you can do synthetic monitoring, everything you want to do. We'll use your monitoring, all of it. Metrics, all of it. And you can use the same system for this. So this was sort of a powerful concept. Like not only is it like the best in leading log system, it also provides everything you need for complete observability. And because it's based on this open platform, you can extend it to a number of different scenarios. So this is important. Like a lot of the different observability companies provide you something that's sort of packaged and as long as you're trying to do what it wants to support, it's great. But with Elastic, you have this flexible data architecture that you can use for anything. So companies use it to monitor assembly lines. They use it to monitor dish networks, for example. Use it to not only manage their fleet of servers, they also use it to manage all their devices. So 25 million desktop devices. So observability systems like that, they can do a number of different scenarios. I think that's a powerful thing. It's not just about how do you manage your servers? How do you manage the things that are simple? It's how do you manage anything? How do you get observability into anything? So, sorry, when you say complete, okay, you talked about all the different APM, log analytics, tracing, metrics, and also end-to-end, is that? So could you talk about that component of complete? So, you know, if you're trying to find an issue, like that you have some metric that goes into alarm, you want to have a metric system that has alarming. Once that metric goes in alarm, you're going to want to dig into your log. So you're going to want it to take you to the area of your logs that has that issue. Once you get to there, you're going to want to find the trace ID that takes you to your traces and looks at sort of profiling and perform distributed tracing information. So a system that can do all of that end-to-end is a powerful solution. So it not only helps you track things end-to-end across the different signals that you're monitoring, but it actually helps you remediate more quickly. And the other thing that Elastic does is unique is a lot of ML in this. So not only helping you find the information, but surfacing things before you even know them. So anomaly detection, for example, helps you know about something before you even realize that there's an issue. So you should pay attention to this because it's anomalous. So a lot of systems help you find something if you know what to look for. But we're trying to help you not only find the things that you know to look for, but help you find the things that you didn't even think to know about. You didn't even think to know about. And it's fair to say one of your differentiators is you're open, open source. I mean, maybe talk about the Elk Stack a little bit and how that plays. Yeah, well, so the great thing about this is we've extended that openness to both security and to observability. An example of this on the security side is all the detection rules that you use for looking for intrusion. All the detection rules are open sourced and there's an entire community around this. So if you wanted to create a detection rule, you can publish an open source, there's a bunch in GitHub, you can benefit from what the community is doing as well. So in the world of security, you want to be supported by an entire community. Everyone looking for the same kind of issues and there's an entire community around Elastic that is helping support these detection rules. So that approach, wanting to focus on community is differentiating for us. Not just we got you covered as long as you use things from us, you can use it from the entire community. Well, there implies the name Elastic. Yeah, yeah, yeah. Talk a little bit about the influence that the customer has in the product roadmap and the direction. You talked a little bit in the beginning about customers were leading us in different directions. It sounds very Amazonian in terms of following the customers where they go. It actually does, it was one of the things that resonated for me personally is the journey that Elastic took to observability and security was customer led. So we started looking at what customers were doing and realized that they were taking us into log analytics. They were taking us into APM. They were taking us into these different solutions. And yeah, it is an Amazonian thing so it resonated for me personally. And they're going to continue taking us in new places. Like we love seeing all the novel things that customers do with the platform. And it's sort of one of the hallmarks of a great platform is you can have all kinds of novel things that novel use cases for how people use your platform. And we'll continue to see things. And we may get taken into other solutions as well as we start seeing things emerge, common patterns. But for now we're really excited about security and observability. So what do you see? So security is a big space, right? You see the octave taxonomy and it makes your eyes bleed because there's so many tools in there. Where do you fit in that taxonomy? How do you see and think about the security space and the opportunity for your customers? Yeah, so we began with logs in the security space as well. So SIM, which is intrusion detection and is based on aggregating a bunch of logs and helping you do threat hunting on those logs. So looking for patterns of malicious behavior or intrusion. So we started there and we did both detections as well as just ad hoc threat hunting. But then we started expanding into endpoint protection. So if we were going to have agents on all these different devices that were gathering logs what if we also started providing remediation? So if you had malicious activity that was happening on one of the servers don't just grab the information, quarantine it, isolate it. So that took us into sort of endpoint protection or XDR. And then beyond that we recently got into cloud security as well. So similar to observability, we started with logs but expanded to a full suite so that you can do everything. You can have both endpoint protection. You can have cloud security, all of it from one solution. So security, sorry, security is a very crowded market as well. What's your superpower? What's our superpower? Yeah. I think a lot of it is just the openness. It's the open platform. There's the community around it. People know and love the elastic search Elk stack and use it like we go into businesses all the time and they're familiar, their security engineers are using our product for searching through logs. So they're familiar with the product already and the community behind it. So they're excited about being able to use detection rules from other businesses and stay on top of that and be part of that community. The transparency of that is important to customers. So if you're trying to be the most secure place, the most secure business, you want to basically invest in a community that's going to support that and not be alone in that. Right, absolutely. So much that rides on that. Favorite customer example that you think really, really articulates the value of elastic, its openness, its transparency. Well, there's a customer Dish Media, Dish Networks, that's going to present here at Reinvent tomorrow at 1.45 at Mandalay Bay. I'm excited about their example because they use it to manage, I think it's 10 billion records a day across 25 million devices. So it illustrates the scale that we can support for managing observability for a company, but also just sort of the unique use cases that we can use this for set top boxes, for all their customers, and they can track the performance that those customers are having. It's a unique case that a lot of vendors couldn't support, but we can support because of the openness of the platform, the open data architecture that we have. So I think it illustrates the scale that we support, the elasticity, but also the openness of the data platform. Awesome, and folks can catch that tomorrow, 1.45 p.m. at the Mandalay Bay. Last question for you, Ken, is, you have a bumper sticker. A bumper sticker. A bumper sticker, you're going to put it on your fancy, sexy new car, and it's about elastic. What does it say? Helping you get answers out of data. So, yeah. Love it, love it. Brilliant, short and sweet. Ken, it's been a pleasure having you on the program. It's been a pleasure being here, thank you. Thank you so much for sharing your journey with us as an Amazonian, now into elastic, what elastic is doing from a product perspective. We will keep our eyes peeled, as Dave was saying. The data show is really strong, spending momentum, so well done. Thank you very much. Good to meet you. Our pleasure. For our guest and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.