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’.
The content discusses the importance of monitoring micrometrics to effectively forecast application performance and availability, particularly focusing on memory, thread, network, and storage metrics. By analyzing metrics like garbage collection throughput, thread states, and IOPS, organizations can identify potential issues early, enhancing application reliability and performance.
The article discusses the limitations of CI/CD pipelines, which primarily analyze macro-level metrics, in identifying performance issues like OutOfMemoryError. It emphasizes the importance of micrometrics—such as garbage collection throughput, thread states, and memory waste—in monitoring applications to preemptively address performance problems and improve software quality in production.
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.