GCeasy is a GC log analysis tool that enhances application performance by identifying and resolving garbage collection issues, leading to improved response times and reduced operational costs. Organizations using GCeasy report significant performance gains and cost savings. Case studies show reduced response times, increased throughput, and minimized downtime, demonstrating its value in optimization.
A major insurance company improved application performance by tuning Garbage Collection (GC). They identified consecutive Full GC events as the bottleneck and explored three solutions. By increasing the heap size and adjusting GC settings, they significantly enhanced GC efficiency, resulting in a 23% increase in application throughput, a 15% reduction in response time, and a 50% decrease in CPU usage.
GC logs are vital for reducing GC pause time, predicting memory issues, and improving application response time. Enable GC logs with specific settings, avoid log file rotation, and monitor logs regularly on all production JVMs to gain valuable insights for performance improvement.
This is an investigative piece on the performance of string deduplication in different versions of Java. The investigation compared Java versions 11, 17, and 21 and their ability to remove duplicate strings. It utilized a WebCrawler application and JMeter load testing to gather data. The findings revealed that Java 11 outperformed versions 17 and 21, eliminating 34.3% of duplicates in 1,264.442 milliseconds. However, newer versions showed a decline in performance, deduplicating fewer strings over longer periods of time.
The post discusses optimizing a Java application used for controlling warehouse robots, which faced performance issues due to long Garbage Collection (GC) pauses. By analyzing the GC log, it identified a large heap size and the CMS GC algorithm as culprits. Switching to the G1 GC algorithm reduced GC pauses significantly, enhancing application performance without major structural changes.
Shenandoah GC enhances Java application's performance by concurrently managing garbage collection with application threads, aiming for low pause times. This is accomplished through region-based memory management and various tuning parameters. Ideal for low-latency, large heap, and highly concurrent applications, Shenandoah offers modes and heuristics for optimizing performance. Analyzing GC logs aids fine-tuning.
This article compares the Garbage Collection (GC) performance of OpenJDK and GraalVM. GraalVM's concurrent, generational collector outperforms OpenJDK by exhibiting higher throughput (99.947%) and lower average pause times (450 ms vs. 2.5 secs). It concludes that GraalVM's GC mechanism is more efficient in managing memory, benefiting application performance.
JAX London is an annual conference for Java and Software Architecture enthusiasts, taking place every October. In 2022, architect Ram Lakshmanan discussed the significant financial waste enterprises incur from ineffective garbage collection, emphasizing the importance of optimization for cost savings and enhanced customer experience.
A leading automobile manufacturer enhanced their middleware platform's response time by 49.46% through optimizing garbage collection with the GCeasy tool, reducing average response time from 1.88 seconds to 0.95 seconds. This adjustment, achieved without code modifications, also decreased transactions exceeding 25 seconds from 0.7% to 0.31%.