There are a good number of articles that articulate functional differences between HashMap, HashTable and ConcurrentHashMap. This post compares the performance behavior of these data structures through practical examples. If you don't have patience to read the entire post, here is bottom line: When you confront with the decision of whether to use HashMap or... Continue Reading →
java.lang.ClassLoader#loadClass() API is used by 3rd party libraries, JDBC Drivers, frameworks, application servers to load a java class into the memory. Application developers don’t use this API frequently. However when they use the APIs such as ‘java.lang.Class.forName()’ or ‘org.springframework.util.ClassUtils.forName()’, they internally call this 'java.lang.ClassLoader#loadClass()' API. Frequent usage of this API amongst different threads at runtime... Continue Reading →
When we launch applications, we specify the initial memory size and maximum memory size. For the applications that run on JVM (Java Virtual Machine), initial and maximum memory size is specified through ‘-Xms’ and ‘-Xmx’ arguments. If Java applications are running on containers, it's specified through ‘-XX: InitialRAMPercentage’ and ‘-XX: MaxRAMPercentage’ arguments. Most enterprises set... Continue Reading →
In this post let's discuss an interesting memory problem we confronted in the production environment and how we went about solving it. This application would take traffic for a few hours after that it would become unresponsive. It wasn't clear what was causing the unresponsiveness in the application. Technology stack This application was running on... Continue Reading →
Java developers tend to use 'java.util.UUID#randomUUID()' API, to generate a UUID (Universally Unique Identifier) number (i.e., 'b8bbcbed-ca07-490c-8711-5118ee0af2f9'). Under certain circumstances, using this API can affect your application’s availability. Let’s discuss this API in this post with a real-world example. How does 'java.util.UUID#randomUUID()' API works? java.util.UUID#randomUUID() API internally uses 'entropy' in the operating system to generate... Continue Reading →
When you tune Garbage collection performance, you are not only improving Garbage collection pause time but also the overall application's response time and reducing cloud computing cost. Recently we helped to tune the Garbage collection behavior of a popular application. Just by making a minor change, it resulted in a dramatic improvement. Let's discuss this... Continue Reading →
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'Load Average' is an age-old metric reported in various operating systems. It's often assumed as a metric to indicate the CPU demand only. However, it is not the case. 'Load Average' not only indicates CPU demand, but also the I/O demand (i.e., network read/write, file read/write, disk read/write). To prove this theory, we conducted this... Continue Reading →
Coming soon..
CPU consumption in Unix/Linux operating systems are studied using 8 different metrics: User CPU time, System CPU time, nice CPU time, Idle CPU time, Waiting CPU time, Hardware Interrupt CPU time, Software Interrupt CPU time, Stolen CPU time. In this article let us study about ‘waiting CPU time’. What is ‘waiting’ CPU time? Waiting CPU... Continue Reading →
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