Distributed Java: Jobs, Locks & Reliability

Dear Java Community,

We’re excited to invite you to the next OpenValue Meetup on September 17th in Düsseldorf!

How do you keep your distributed applications running reliably when the workload gets real? Join us at our office at Am Wehrhahn 41, 40211 Düsseldorf, for an evening exploring background job processing with JobRunr and the challenges of coordinating scheduled jobs across multiple Spring pods. We’ll dive into scalable, resilient approaches for asynchronous processing, retries, persistence, and distributed locking—plus the race conditions and failures that can hide until production. Come learn how to stop reinventing infrastructure and build distributed systems that behave predictably under load!

We’ll take care of refreshing drinks and tasty food—you just bring your curiosity and questions!

👉 Please RSVP to confirm your attendance.

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🗓️ Agenda
17:30 – Doors open / Walk-in
18:00 – First Talk
18:45 – Break
19:00 – Second Talk
19:45 – Drinks & Discussions

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🎤 Talks
Lock, Stock, and Two Smoking Pods: Locking in Distributed Spring Applications
by Konstantin Belinski
Three pods. One scheduled job. One database. What could go wrong?
Clean logs, monitoring green - and yet customers receive duplicate emails, records silently disappear, and that critical nightly cleanup job quietly failed while your storage filled up overnight. These aren't exotic edge cases. Distributed systems and scalability don't come without cost. More instances mean more potential for race conditions, deadlocks, and coordination failures that only surface under real load - long after the code looked fine in review.

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A Java 8 lambda and JobRunr is all you need for distributed (batch) processing!
by Ronald Dehuysser
Are you struggling with CPU-intensive tasks, high I/O work, or do you need to schedule background jobs without blocking the rest of your system? I often see teams building a scheduling solution themselves, severely underestimating the complexity of running jobs asynchronously. A costly endeavour, especially with a simple, free and open-source solution readily available.

During this fun session, I will introduce you to JobRunr: the ultimate open-source library for background processing in Java, recommended by ThoughtWorks. By transforming Java lambdas into distributed background tasks, JobRunr allows you to run any job at any time and on any JVM. We'll delve into its diverse features such as job persistence, automatic retries, scalability (hello k8s), and the integrated dashboard to provide you with a good grasp of the possibilities. Oh, and did you know it also works on GraalVM?

After this session, you’ll have a good idea of what JobRunr is, how it does its magic and how it will allow you to focus on delivering value to your end users instead of implementing scheduling over and over again.

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We’re looking forward to another great evening of learning, sharing, and networking—don’t miss out!

See you on September 17th! 👋