<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Apache Kafka on Victor Laurance - Software Engineer</title><link>https://laurance.dev/en/tags/apache-kafka/</link><description>Recent content in Apache Kafka on Victor Laurance - Software Engineer</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 09 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://laurance.dev/en/tags/apache-kafka/index.xml" rel="self" type="application/rss+xml"/><item><title>Apache Kafka with Java: Architecture, Idempotence, and End-to-End Resilience</title><link>https://laurance.dev/en/blog/kafka-java/</link><pubDate>Fri, 09 Oct 2026 00:00:00 +0000</pubDate><guid>https://laurance.dev/en/blog/kafka-java/</guid><description>&lt;p>What actually happens when your application executes &lt;code>kafkaTemplate.send(...)&lt;/code>?&lt;/p>
&lt;p>If your answer is simply &amp;ldquo;the message arrives in a queue and a worker processes it&amp;rdquo;, you are operating Apache Kafka under the mental model of a traditional message broker like RabbitMQ or AWS SQS. Kafka is fundamentally different: it is an &lt;strong>immutable, append-only, distributed commit log&lt;/strong>.&lt;/p>
&lt;p>This difference changes everything: how you partition workloads, how consumers scale, how you guarantee delivery order, and, most importantly, &lt;strong>how you prevent duplicate processing or data loss when networks glitch or nodes crash&lt;/strong>.&lt;/p></description></item></channel></rss>