Show Notes
Episode description: Ludovic Orban (Jetty Maintainer and Performance Engineer at WebTide) joins Marco to break down what “web scale” really means, why most systems don’t need Google-level architecture, and how modern Java servers achieve massive throughput. From Jetty’s design philosophy to multi-core CPU realities, distributed transactions, Terracotta’s wild JVM clustering experiments, and the limits of AI-generated code, this episode dives deep into how high-performance Java is built today. 💡 In this episode: What “web scale” actually means for real-world systems
Jetty vs Tomcat and how Jetty became a fast, modern web server
CPU evolution, memory bottlenecks, and multi-core performance
Distributed transactions, XA pitfalls, and compensating patterns
Terracotta’s clustered JVM: engineering lessons and war stories
Why developers struggle with performance (and how to learn it)
AI, coding assistance, and why Ludovic doesn’t trust generated code
⏱️ Timestamps: (00:00) Teaser (01:10) Who is Ludovic Orban? (02:04) What “web scale” really means, and who actually needs it (03:54) How hardware changes reshaped software performance (06:28) Cloud, containers, and why performance still matters (07:28) Jetty vs Tomcat: history, adoption & performance (10:47) What makes Jetty “fast” in practice (13:21) How the Jetty team prioritizes performance (15:10) Recent work: fixing complex HTTP/2 bugs (16:38) How WebTide supports customers beyond Jetty issues (17:52) Bitronix: Why Ludovic built his own transaction manager (20:45) Open-source challenges. The rise and fall of Bitronix (24:19) Distributed transactions vs compensating transactions (27:07) Where to learn more: Atomikos and modern approaches (28:25) Terracotta: clustering JVMs and wild engineering stories (31:20) What Terracotta taught him about the JVM (33:48) Real-world Java performance mistakes developers make (40:22) Why learning performance is so hard (45:40) Kubernetes, abstraction, and performance visibility (48:50) Hardware that excites Ludovic: Oxide Computer (50:42) His take on AI and why he doesn’t trust generated code (53:30) Lessons from Jetty, Terracotta, Bitronix, and Quartz (56:10) Rapid-fire questions (01:01:15) Giveaway and outro
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