A major automobile manufacturer significantly enhanced its middleware platform by optimizing garbage collection performance, achieving a 49.46% reduction in overall response time from 1.88 seconds to 0.95 seconds. This improvement was attained solely through adjustments to garbage collection settings, eliminating the need for code refactoring or costly changes.
Uber successfully saved 70,000 cores across 30 critical services by optimizing Go's Garbage Collection (GC) through a semi-automated tuning mechanism. This effort resulted in significant CPU utilization improvements, notably 65% in observability services and 30% in Uber Eats. GC tuning is essential for efficient resource management and application performance.
The Dell Boomi Core servers experienced a performance outage in the early morning at 4 a.m. Below are the symptoms observed: Dell Boomi wasn’t responding to any incoming requests CPU consumption was skyrocketing to 100% Entire Dell Boomi cluster had to be recycled to recover from the unresponsiveness. In this post, we have shared the... Continue Reading →
Laurentiu Spilca, a talented Java and Spring developer, authored "Troubleshooting Java," focusing on code investigation techniques to optimize and debug JVM applications. The book offers practical insights and real-world examples, including effective use of the yCrash-fastThread tool for analyzing thread dumps, quickly identifying issues like deadlocks to enhance Java app performance.
We express our gratitude to Entwinkler.de JavaMagazin for translating our article ‘Simulating and troubleshooting deadlocks in Kotlin’ into German. It is an honor to have it published in their December 2022 issue as ‘Simulation und Fehlerbehebung von Deadlocks in Kotlin’.
Prabhakar Jonnalagadda, a performance architect at Oracle, addresses application performance issues characterized by crashes and degraded performance. He analyzes GC logs with GCeasy and adjusts JVM arguments to enhance performance. He emphasizes that tuning options are unique to each case and engineers must explore various approaches for optimal solutions.
This article discusses optimizing garbage collection (GC) performance in applications, highlighting its importance for reducing pause times, improving response times, and lowering cloud costs. Key performance indicators like GC pause time, throughput, and CPU usage are analyzed. A case study illustrates how reducing the young generation size significantly improved GC metrics and overall performance.
