<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Observability on JAVAPRO International</title><link>https://javapro-en.svenruppert.com/tags/observability/</link><description>Recent content in Observability on JAVAPRO International</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 11 Jun 2026 07:00:01 +0000</lastBuildDate><atom:link href="https://javapro-en.svenruppert.com/tags/observability/index.xml" rel="self" type="application/rss+xml"/><item><title>Automating JVM Thread Dump Analysis with AI: Practical Observability for Java on Amazon ECS and EKS</title><link>https://javapro-en.svenruppert.com/automating-jvm-thread-dump-analysis-with-ai-practical-observability-for-java-on-amazon-ecs-and-eks/</link><pubDate>Thu, 11 Jun 2026 07:00:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/automating-jvm-thread-dump-analysis-with-ai-practical-observability-for-java-on-amazon-ecs-and-eks/</guid><description>&lt;p&gt;Imagine the following scenario: a Java service that ran flawlessly yesterday suddenly starts consuming 90% CPU, barely responding to user requests. Users encounter timeouts, and the operations team is under immediate pressure to triage the incident. In these situations — whether the application appears stuck or CPU saturation has occurred — one of the most powerful diagnostic assets available is the thread dump. A thread dump captures the state of all JVM threads at a specific point in time, showing execution states, stack traces, and lock contention — the raw material needed to understand what the runtime is &lt;em&gt;actually doing&lt;/em&gt;.&lt;/p&gt;</description></item><item><title>LangChain4j Production-ready features with Quarkus</title><link>https://javapro-en.svenruppert.com/langchain4j-production-ready-features-with-quarkus/</link><pubDate>Thu, 20 Nov 2025 07:00:02 +0000</pubDate><guid>https://javapro-en.svenruppert.com/langchain4j-production-ready-features-with-quarkus/</guid><description>&lt;p&gt;Have you already read the article &amp;ldquo;&lt;strong&gt;Build AI Apps and Agents in Java: Hands-On with LangChain4j&amp;rdquo;&lt;/strong&gt; by Lize Raes in the “30 Years of Java” edition - part 1 - of that magazine? If so, you&amp;rsquo;re familiar with what LangChain4j is for.&lt;/p&gt;
&lt;p&gt;If not, don&amp;rsquo;t worry—I included the link at the end of this article. I recommend reading it before continuing with this one.&lt;/p&gt;
&lt;p&gt;In this article, we&amp;rsquo;ll explore and demonstrate important LangChain4j production-ready features using Quarkus, a lightweight Java framework that integrates seamlessly with LangChain4j.&lt;/p&gt;</description></item><item><title>Observability Landscape in Java</title><link>https://javapro-en.svenruppert.com/observability-landscape-in-java/</link><pubDate>Wed, 13 Aug 2025 07:00:03 +0000</pubDate><guid>https://javapro-en.svenruppert.com/observability-landscape-in-java/</guid><description>&lt;p&gt;Java has become a well-established and widely adopted language. As software systems became more complex with the shift to microservices, Java observability tools evolved to meet new demands. It has evolved to address these new challenges, offering improved capabilities for monitoring, tracing, and debugging. This article explores the evolution of Java observability and its adaptation to modern cloud-native solutions. Lets discuss how they have shaped into the landscape of observability in Java applications today.&lt;/p&gt;</description></item></channel></rss>