We appreciate Entwinkler.de JavaMagazin for translating and publishing our article ‘Simulating and troubleshooting deadlocks in Kotlin’ in German. It’s a privilege to see our work featured in a print magazine, specifically the December 2022 issue, under the title ‘Simulation und Fehlerbehebung von Deadlocks in Kotlin’.
ConFoo Montreal is a conference for developers featuring Ram Lakshmanan, who presents on capturing 16 key artifacts during production problems, ranked 5th out of 155 sessions. The session emphasizes the importance of diagnostic information for troubleshooting and discusses effective tools for analyzing captured artifacts. Slide deck available for reference.
The author reflects on the evolution from monolithic to microservice architecture over 20 years. Initially, a monolithic application efficiently managed critical services on modest memory. In contrast, modern microservices often require significantly larger memory allocations, leading to concerns about resource consumption, response times, and overall complexity, despite their development advantages.
The Java Virtual Machine (JVM) generates three essential artifacts for performance optimization and troubleshooting: Garbage Collection (GC) log, Thread Dump, and Heap Dump. Each artifact helps analyze memory performance, thread states, and memory allocation issues. Various tools assist in generating and examining these artifacts, aiding in effective problem resolution.
Performance tests in enterprises often report macro metrics like CPU utilization and response times. However, these metrics can miss acute performance degradations and hinder troubleshooting. Incorporating micro metrics, such as Garbage Collection pause times and thread states, provides deeper insights and facilitates better performance management and debugging efforts for development teams.
Solves all OutOfMemoryError problems. There are 8 flavors of java.lang.OutOfMemoryError.