Roundtable: Concurrency
summary
Panel reports specific failures and fixes: a leader-queue design that works in Go fails on Java until manual memory fences and hand-rolled synchronization replace naive atomics; an accounting pipeline deadlocks on a mutex and costs a week to debug; adopting Coz profiler surfaces threading hotspots; teams use kotlinx.coroutines and debate Project Loom vs fibers; production choices favor Scylla/Cassandra/Mongo and Redis for queues, Kubernetes for scaling, and often solving concurrency by moving work to multiple single-threaded instances rather than complex in-process locking.
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chapters (9)
- 0:00Introduction
- 4:23Painful multithreading experiences
- 10:05Java and Kotlin sync primitives
- 16:29When to use actor model
- 23:38Actors vs coroutines comparison
- 32:15Parallelism versus concurrency
- 43:42Memory model and thread safety
- 51:03Modern Java concurrency
- 58:54Conclusion
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