Show Notes
Ronald Dehuysser, creator of JobRunr, joins Marco to talk about distributed job scheduling in Java, building a high-throughput background processing framework, and turning an open-source side project into a profitable business. They dive into what really happens when microservices lack distributed tracing, why dead letter queues can silently lose invoices, how JobRunr scales to thousands of jobs per second, and what it takes to monetize open source in the Java ecosystem. 💡In this episode: Distributed job scheduling and background processing in Java
JobRunr architecture and high-throughput performance
Quartz vs modern scheduling approaches
Retries, exponential backoff, and reliability patterns
Dead letter queues and observability challenges
Microservices vs monoliths in enterprise systems
Monetizing open source and pro licensing models
Enterprise sales and scaling a developer product
Burnout, sustainability, and building a team
AI, LLMs, and the future of junior developers
⏱️Timestamps (00:00) Teaser(00:48) Who's Ronald Dehuysser and what's JobRunr(01:37) From enterprise dev to freelancing (and switching to .NET)(11:19) Job scheduling pain and birth of JobRunr(16:21) Quitting, COVID, and building the first version(28:48) First customers and monetizing open source(40:13) Big enterprise deal and going full-time(47:16) Burnout, Vipassana, hiring, and building a team(53:20) Sustainability features and the future of JobRunr(56:08) AI, junior developers, the future of coding(01:07:28) Giveaway and Rapid-fire questions
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