The Marco Show

J. B. Rainsberger, TDD coach and software consultant, joins Marco to challenge common assumptions about software testing. They discuss why JB argues that “integrated tests are a scam,” how testing choices affect design and refactoring, and what teams get wrong when they rely too heavily on end-to-end tests. The conversation draws on decades of real-world experience working with development teams of all sizes.💡 Topics in this episode:What “integrated tests” really are and why they cause problemsMicro tests, fast feedback, and confidence-driven testingWhen deleting tests is the right decisionHow tests create pressure on system designCollaboration and contract tests explainedWhy there is no single testing best practicePractical advice for junior and senior developersNew episodes every other Wednesday. Subscribe for more developer-focused conversations.⏰ Timestamps:(00:00) Teaser(01:24) Intro(02:44) How J. B. got into testing(06:12) What “integrated tests” actually mean(10:42) Stop asking “what’s the right test size?”(13:22) Removing irrelevant details from tests(15:30) Refactoring, coupling, and deleting tests(18:08) “There’s no best practice.”(23:52) Old TDD books and timeless ideas(26:01) Collaboration and contract tests explained(33:53) “99.5% of your tests can be micro tests”(46:21) Do you want to be right or solve the problem?(01:00:48) Advice for junior developers(01:19:32) Testing strategy distilled(01:23:58) Manual QA testing(01:29:44) Giveaway(01:33:15) Rapid fire and outro🎥 Watch the full episode on YouTube: https://youtu.be/j0NjFsb-at8

The first season of The Marco Show has officially come to an end! In this Christmas special episode, we’re announcing all of our giveaway winners and wrapping up the season with a fun Q&A with Marco.🎁 Giveaway winners:If you’re one of the winners featured in this episode, please reach out to us at [email protected] and let us know what you’d prefer: a 1-year license to one of our JetBrains products, or a coupon for the JetBrains merch store.Timestamps: (00:00) Season Finale Intro & What to Expect(00:34) LLMs with Jodie Burchell: giveaway winner(01:08) Software performance with Casey: giveaway winner(01:39) Hibernate with Gavin King: giveaway winner(02:15) Flyway with Axel Fontaine: giveaway winner(02:45) SQL with Torben: giveaway winner(03:16) Quarkus with Kevin Dubois: giveaway winner(03:46) Jetty with Ludovic: giveaway winner(04:18) ByteBuddy with Rafael: giveaway winner(04:52) How to claim your prize(05:08) Q&A with Marco(09:35) Outro and meet the teamThank you to everyone who watched, listened, and supported the show this season. We truly appreciate it. See you next year!New episodes every other Wednesday. Subscribe for more developer-focused conversations. 🎥 Watch the full episode on YouTube: https://youtu.be/hZemYWNKa6I

Rafael Winterhalter, creator of ByteBuddy and long-time Java consultant, joins Marco to break down the hidden world of JVM bytecode instrumentation. They discuss how ByteBuddy powers tools like Mockito and Hibernate, why legacy Java still dominates enterprise systems, and what it’s really like maintaining a massive open-source project as a single developer.💡 Topics in this episode:How ByteBuddy works and why frameworks rely on itJVM bugs, JIT issues, and surprises from instrumentationSupporting legacy Java (5, 6, 8…) in modern environmentsOpen-source sustainability and avoiding burnoutJava modules, unsafe, and evolving with new JDK releasesRethinking Java build tools and software engineering complexity🕑 Timestamps:(00:00) Intro(01:10) Rafael’s background & the origin of ByteBuddy(03:00) What ByteBuddy does and why it matters(04:32) Replacing CGLIB and early challenges(07:05) ByteBuddy’s design philosophy(09:15) Mockito, Hibernate and real-world adoption(13:14) Open source reality(15:48) Performance myths and JVM behavior(18:47) JVM bugs, JIT issues and instrumentation pitfalls(21:11) Supporting legacy Java in enterprise(23:56) Testing ByteBuddy across many JDKs(25:53) Why companies still run Java 5/6(28:25) Engineering vs economics(30:39) Modules, unsafe and evolving with Java(36:12) Maintaining a one-person project(39:31) Conferences and developer evangelism(42:02) Consulting vs product engineering(49:51) Burnout and sustainability(52:02) Thoughts on AI in software development(57:13) Rethinking Java build tools(01:05:07) Build security and dependency risks(01:10:16) Giveaway(01:10:48) Rapid fire and outroNew episodes every other Wednesday. Subscribe for more developer-focused conversations.🎥 Watch the full episode on YouTube: https://youtu.be/AzfhxgkBL9s

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 systemsJetty vs Tomcat and how Jetty became a fast, modern web serverCPU evolution, memory bottlenecks, and multi-core performanceDistributed transactions, XA pitfalls, and compensating patternsTerracotta’s clustered JVM: engineering lessons and war storiesWhy 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 outroNew episodes every other Wednesday. Subscribe for more deep, developer-focused conversations.🎥 Watch the full episode on YouTube: https://youtu.be/fJvg5zTKHeE

Kevin Dubois (IBM Developer Advocate, Quarkus Team) joins Marco to explore how Quarkus is reinventing Java for the modern cloud era, and why it’s not about killing Spring Boot. From startup times to developer experience, microservices, AI, and GraalVM, this episode dives into where Java is heading in 2025 and beyond.💡 Topics in this episode:The origins of Quarkus and why it existsSpring Boot dominance and migration trendsHot reload, Dev UI, and developer experienceCloud-native Java, containers, and serverlessGraalVM and the future of native JavaJava’s role in the age of AINew episodes every other Wednesday. Subscribe for more deep, developer-focused conversations.🎥 Watch the full episode on YouTube: https://youtu.be/IRqTbgC2JLU⏱️ Timestamps:(00:00) Intro(01:12) Why Quarkus was created (it’s not about killing Spring)(04:45) How Quarkus compares to Spring Boot today(08:30) Developer experience: hot reloads, Dev UI, and that “aha” moment(13:05) Quarkus in the cloud: Kubernetes, containers, and serverless(18:20) Native compilation vs JVM: when (and when not) to use it(24:00) MicroProfile, Jakarta EE, and open specs(28:35) The future of Java: monoliths, microservices, and AI(33:10) How IBM is investing in Quarkus and the Java ecosystem(37:25) Agentic AI, LangChain4J, and practical use cases(42:10) Rapid-fire questions(46:15) Giveaway question + closing thoughts