Garbage Collection Optimization: High Throughput and Low Latency Java Applications
Article Summary
LinkedIn Engineering cut their tail latency by 75% through systematic garbage collection tuning. Here's their playbook for high-performance Java apps.
Swapnil Ghike shares how LinkedIn's team optimized GC settings for their next-generation feed data platform serving thousands of requests per second. The article breaks down their methodical approach from baseline measurements to production-ready configuration.
Key Takeaways
- ParNew/CMS outperformed G1 collector for their workload, showing lower CPU and memory overhead
- Tuning CMSInitiatingOccupancyFraction to 92 and MaxTenuringThreshold to 2 reduced pause frequency
- Setting ParGCCardsPerStrideChunk to 32768 dropped young gen pauses from 80ms to 50ms
- Final config achieved 60ms p99.9 latency with CMS cycles running just once per hour
- AlwaysPreTouch flag and vm.swappiness=0 eliminated runtime page faulting penalties
Critical Insight
LinkedIn achieved 40-60ms GC pauses every 3 seconds and 60ms p99.9 latency through data-driven tuning of ParNew/CMS settings.
