Eclipse MAT, Heaphero are all popular java tools to analyze large size heap dumps. Recently we ran in to an interesting problem when trying to analyze a heap dump file in Eclipse MAT. Tool was crashing because of missing font 😊. We thought we will share with you what we found out.
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One of the widely wasted resources in the world today is: Memory. Due to inefficient programming, surprising (sometimes ‘shocking’) amount of memory is wasted. We see this pattern repeated in several enterprise applications. To prove this case, we conducted a small study. We analyzed the famous spring boot pet clinic application to see how much memory it is wasting. This application has been designed by the community to show how the spring application framework can be used to build simple but powerful database-oriented applications.
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Recently we experienced an interesting production problem. This application was running on multiple AWS EC2 instances behind Elastic Load Balancer. The application was running on GNU/Linux OS, Java 8, Tomcat 8 application server. All of sudden one of the application instances became unresponsive. All other application instances were handling the traffic properly. Whenever the HTTP request was sent to this application instance from the browser, we were getting following response to be printed on the browser.
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In this article, we have attempted to answer the most common questions around System.gc() API call. We hope it may be of help.
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Should I be running my application with few instances (i.e. machines) with large memory size or a lot of instances with small memory size? Which strategy is optimal? This question might be confronted often. After building applications for 2 decades, after building JVM performance engineering/troubleshooting tools (GCeasy, FastThread, HeapHero), I still don’t know the right answer to this question. At the same time, I believe there is no binary answer to this question as well. In this article, I would like to share my observations and experiences on this topic.
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JVM has provided helpful arguments to deal with OutOfMemoryError. In this article we would like to highlight those JVM arguments. It might come handy for you when you are troubleshooting OutOfMemoryError. Those JVM arguments are:
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Troubleshooting OutOfMemoryError or any memory related problem is done in manually even in 2019. Troubleshooting and identifying the root cause of OutOfMemoryError can even be automated, by following below mentioned 3 steps:
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There are a few distinct differences and subtle nuances between 32-bit JVM and 64-bit JVM. We thought we will try to clarify them through this question & answer article
Continue reading “DOES 32-BIT OR 64-BIT JVM MATTER ANYMORE?”
Eclipse Memory Analyzer (MAT) is a powerful tool for heap dump analysis. It has several great features to debug memory problems effectively. ‘Incoming references’ and ‘outgoing references’ is one such feature. In this article let’s discuss about ‘incoming references’, ‘outgoing references’ and difference between them.
Continue reading “ECLIPSE MAT – INCOMING REFERENCES, OUTGOING REFERENCES”
