Consistently increasing heap valleys might indicate either an improper heap configuration or a memory leak. Detect Memory Leaksīy monitoring the JVM heap and memory pool, you can identify potential memory leaks. A heap that is too big will delay garbage collection and stress the operating system when needing to page the JVM process to cope with large amounts of live data.A heap that is too small will cause excess garbage collections and increases the chances of OutOfMemory exceptions.The size of the JVM heap can affect performance and should be adjusted if needed: You can view heap information in the metric browser or in the Memory tab for a given node as directed in Monitoring JVM Information. This section focuses on managing the heap. Memory management includes managing the heap, certain memory pools, and garbage collection. Implemented as part of JVM Crash Guard, JVM crash is an event type that you can activate to provide the critical information you need to expeditiously handle JVM crashes. A JVM crash is because it may be a sign of a severe runtime problem in an application. Using the Machine Agent, when a JVM crash occurs on a machine or node, you can be notified almost immediately and take remediation actions. You can also create additional persistent JMX metrics from MBean attributes.
#Java memory monitor how to#
Once you have a health rule, you can create specific policies based on health rule violations. One type of response to a health rule violation is an alert. See Alert and Respond for how to use health rules, alerts, and policies. You can set up health rules based on JVM or JMX metrics. In the Metric Browser, click Application Infrastructure Performance and expand the JVM folder for a given node to access information about Garbage Collection, Classes, Process CPU, Memory, and Thread use. In the JMX Metrics subtab metric tree, click an item and drag it to the line graph to plot current metric data.
In the Tiers & Nodes dashboard, see the following tabs for JVM-specific information: You can view JVM performance information from the Tiers & Nodes dashboard or from the Metric Browser. You can configure additional monitoring for: On a per-node basis, AppDynamics reports: Total classes loaded and how many are currently loaded.The key performance indicators that AppDynamics focuses on as most useful for evaluating performance include: JVM Key Performance IndicatorsĪ typical JVM may have thousands of attributes that reflect various aspects of the JVM's activities and state. This page provides an overview of some of the tools AppDynamics provides for monitoring Java applications and troubleshooting common issues.