The garbage collection phase in Java applications is important for keeping performance high. Configuring garbage collector threads, including concurrent and parallel threads, can improve application performance. Be careful with manual thread configuration to avoid performance problems. Analyzing thread dumps can help monitor and enhance performance by identifying problem areas and fine-tuning settings.
Containerized environments are crucial for modern app development, especially in the cloud. This article looks at how garbage collection threads affect containerized environments. It stresses the importance of using resources wisely and talks about controlling these threads to improve performance, especially with Docker and CPU allocation.
This article looks at the complexities of multithreading in Java, focusing on how threads are managed within the JVM. It explains how to handle and understand the extra threads created when running applications and highlights the importance of JVM-specific threads and their roles. It also covers garbage collection and ways to optimize threads.
This article gives an overview of common garbage collection phases such as Mark, Sweep, Evacuation, Young GC, and Full and Old GC. It explains their implementation, impact, and trade-offs. Understanding these phases is essential for optimizing garbage collection in applications. Developers can use GC logging for studying behavior and making necessary adjustments.
This article talks about how the JVM stores objects in memory. It explains how alignment, padding, and memory usage are related. It also talks about how the alignment can be adjusted and those changes affect the performance, highlighting how managing memory and object sizes can be tricky.
This post shares an experience in optimizing a Java application controlling warehouse robots, addressing performance issues due to long Garbage Collection (GC) pauses. By analyzing GC logs, the team identified excessive heap size and the CMS algorithm as causes. Switching to the G1 GC algorithm successfully reduced pause times, improving overall application performance.
This post examines configuring Virtual Threads in a Spring Boot application that calculates the Fibonacci sum for values starting from 10,000. Using JMeter, a load test with 1000 users reveals similar throughput and average response times for both virtual and native threads, highlighting virtual threads' advantage in lower thread usage without performance gain for CPU-intensive operations.
Spring Boot is a popular Java framework that allows developers to minimize boilerplate code and easily configure applications. By leveraging Virtual Threads, developers can enhance thread management without extensive rewrites. Configuration involves setting properties in application files and using the @ConditionalOnProperty annotation to toggle between Virtual and Native Threads seamlessly.
This article discusses improving application performance by optimizing String memory usage in Java. It explains String allocation methods, the benefits of String.intern(), and introduces String deduplication during garbage collection. The analysis highlights trade-offs between space and time efficiency, urging careful consideration before implementing optimizations based on specific application needs and metrics.
Shenandoah GC enhances Java applications by minimizing pause times through concurrent garbage collection and region-based memory management. It is ideal for low-latency and large heap applications, offering various tuning parameters and modes to optimize performance. Effective analysis of garbage collection logs allows developers to fine-tune Shenandoah for their specific needs.