 Thanks for coming to this lightning talk. It will be approximately five minutes. First question, who does develop with Java these days? Not so many, and this is why I got lightning talk. But as you might have seen from the agenda, it was supposed to be a long talk. So I'm not showing you any demos. I'm not showing you Quarkus. But tomorrow you can find me at the projects booth, at the open telemetry booth, and I have everything with me. I'm happy to show it. OK, my name is Alekhtin Ashev. I'm a serial community builder. You might know me from some CNCF projects or from continuous delivery foundation. But actually, I like developer tools. And when you think about developer tools, about productions, you need observability. Actually, first my observability project was more than 15 years ago. It was oil flow monitoring based on X-ray gamma analysis. So through Russian observability project, and yeah, it works quite well. But of course, for me, the real exposure was when I started working with Mr. Jenkins, because when you work on CI, CD at scale with multiple agents connected, there is a lot of things breaking there. And of course, observability is one of the biggest concerns. And this one, I learned Python because I needed to do Xenos extensions. So fortunately, these days we have open telemetry. And yeah, when the CI breaks, it's a lot of problems. You have to troubleshoot a lot. And you don't have much tools. And this one, observability becomes really important. We had a few collaborations with Doton and other people on CI, CD observability. Maybe you know that there is special seek on CI, CD observability and open telemetry on the CNCF Slack. So this is why I'm happy to discuss this talk and all the ideas. And in Jenkins, we actually invested quite a lot in open telemetry. We got integration that would allow you to investigate not just Jenkins, not just its agents, infrastructure, provisioning, and Kubernetes, et cetera, but also tools underneath, like Maven or Gradle, that would be invoked and would become a part of the same traces. So you would get all the insights, including tests and execution for your projects. And when we talk about that, of course, there are two parts. So we have Jager, we have Prometheus, we have Grafana for all analytics, querying, et cetera. And we have the bad part, which is everything around CI, CD, and connected tooling. Because actually, there is a lot of things that connect and have to fit the data. So on the top part, everything is trivial. You have all the integrations. You have tools like Knative or Rabusta that provide you with all kinds of automation. That's great. On the other side, yes, there is a lot of tools. Every tool is implemented differently in different languages. This is why we have so many SDKs for open telemetry. This is why we have so many aggregation and performance problems, like discussed during the previous talks. And this is what we have to resolve with Java. Because in Java, yes, you have a tool that triggers something, but the most of execution happens somewhere in different tools. So who does use Gradle? Did you know you can build a Golan project with Gradle? Never tried it, but you can. So in Gradle, we have multiple tools that can help you with observability. So there is embedded Gradle scan command. There is Gradle profiler. There is a lot of Java tools and NDEs created over 15 years to allow this observability. There is also the velocity, which is an enterprise tool for that. And last but not least, there is open telemetry integration. So just to show you an example, here's an example of Gradle build scan and velocity. So it's SAS and Freemium for all open source and commercial projects. And there we can analyze all the execution, performance, et cetera. And basically, this information is extended version of open telemetry. It also includes cloud events and profiles and things that are yet to be implemented on open telemetry. And you can see that, actually, I reference open telemetry Java instrumentation. Because actually, open telemetry project is supported by Gradle. And they use open velocity to automate their builds and to speed up delivery for Java components. And if you have Java components in your projects, it's also something I'm happy to discuss, whether it's Gradle or Maven. For open telemetry plugin, there is a plugin that was created by Craig Atkinson. This is Gradle open telemetry integration, mostly for spans. But it also has metrics and logs embedded. So you can submit quite a lot of data. This is an open source project. It's just a Gradle plugin which you enable in your build. And then you get quite a lot of information, including tasks execution. So basically, Gradle in this regard is like a make file or a puzzle where you have a lot of targets. And you have truck of execution for these targets, which might be parallel, sequential, distributed across machines. So it's very important. And same for tests. We also have embedded test reporting. So if you execute tests in your unit test framework, you also get insights right inside open telemetry, which is quite cool. And what is Ms. Maven integration at the moment? And of course, for all the tools, for all the integrations, you just get a single trace. So you start from your GitHub, from pull request, then it goes to Jenkins, or GitHub actions, then it goes to Gradle, build tool, then it goes to Java compiler. And for all of that, you have a single trace, which is the main purpose of that. And if you want to watch examples with Maven on Gradle, just follow the links. Tomorrow, I'm happy to show all the examples live. And also for Golanth, test containers, et cetera. So everything open telemetry and projects I'm working on. Happy to discuss. And join Hotel CI CD Channel if you have a CI CD instance. Because this is where these topics should be discussed. So thank you. And I appreciate your time listening about Java projects.