Community Blog Introduction to Java Virtual Machine (JVM) Performance Tuning

Introduction to Java Virtual Machine (JVM) Performance Tuning

Java Virtual Machine performs excellent and is widely used, in this article, we will introduce the performance tuning for JVM.

JVM tuning is a systematic and complex task. At present, the automatic adjustment under JVMs is very excellent and basic initial parameters can ensure that common applications runs stably. For some teams, application performance may not take a high priority. In this case, the default garbage collector is usually adequate enough to meet the desired requirement. Tuning should be based on your own situation.

JVM tuning mainly involves optimizing the garbage collector for better collection performance so that applications running on VMs can have a larger throughput while using less memory and experiencing lower latency. As what we said above, less memory/lower latency does not necessarily mean that the less/lower the memory/latency is, the better the performance is. It is about the optimal choice.

Performance Tuning Principles

During the tuning process, the three following principles can help us implement easier garbage collection tuning to meet desired application performance requirements.

  1. Minor GC collection principle: Each time Minor GC should collect as many garbage objects as possible to reduce the frequency of Full GC for an application.
  2. GC memory maximization principle: When solving throughput and latency problems, the larger the memory used by the garbage collector, the more efficient the garbage collection and the smoother the application.
  3. GC tuning "two out of three" principle: We should only tune two of the three performance attributes instead of all the three attributes: throughput, latency, and memory usage.

JVM tuning involves continuous configuration optimizations and multiple iterations based on the performance test results. Before each desired system metric is met, each of the previous steps may experience multiple iterations. In some cases, to meet a specific metric, the previous parameters may need to be tuned many times, requiring all the previous steps to be tested again.

In addition, tuning generally starts with meeting the memory usage requirement of applications, then latency and throughput. Tuning should follow this sequence of steps. We cannot invert the sequence of these tuning steps.

java jvm tuning procedure

For the details for each tuning step, please go to How to Properly Plan JVM Performance Tuning.

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The application monitoring function of Application Real-Time Monitoring Service (ARMS) provides the Java Virtual Machine (JVM) monitoring function. It monitors heap metrics, non-heap metrics, direct buffer metrics, memory-mapped buffer metrics, garbage collection (GC) details, and the number of JVM threads. This topic describes the JVM monitoring feature and how to monitor JVM metrics.

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For example, we might observe different performance influences of a JVM feature on different Java applications and different performance results of the same application on difference hardware. Cases like this are far from uncommon. Since it is infeasible for us to run tests for every application and every piece of hardware, we need a systematic approach to estimating the overall performance impact of a new feature on various applications and hardware.

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  1. Low Java object storage density. An object that contains only a boolean attribute takes as many as 16 bytes, where the object header takes 8 bytes, the attribute takes 1 byte, and the padding takes 7 bytes. Actually, one bit (1/8 byte) is enough to store the attribute.
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