Java memory analysis is an important process in checking the performance of a Java application. It helps Java developers ensure the stability of the application by checking the memory consumption. There are several factors to look into when doing memory analysis. But to get to the bottom of this process, it is vital to learn first how memory works.

Splunk Distro for OpenTelemetry is a secure, production-ready, Splunk-supported distribution of the OpenTelemetry project and provides multiple installable packages that automatically instruments your Java application to capture and report distributed traces to Splunk APM (no code changes required!), making it easy to get started with distributed tracing!

Java developers are unlikely to ever suffer from a lack of libraries, utilities, and programs at their disposal. There's no shortage of tools that offer niche as well as fundamental features. However, some tools undoubtedly stand out due to their popularity, usefulness, data representation, and in-tool features. These 8 tools listed below are often listed as some of the best Java development tools available on the market.

A memory leak is a situation where unused objects occupy unnecessary space in memory. Unused objects are typically removed by the Java Garbage Collector (GC) but in cases where objects are still being referenced, they are not eligible to be removed. As a result, these unused objects are unnecessarily maintained in memory. Memory leaks block access to resources and cause an application to consume more memory over time, leading to degrading system performance.

Debugging is the process of identifying and fixing any issues in the source code of a program. Modern IDEs like Eclipse provide debugging tools that make it easier for developers to walk through their code interactively and inspect it to spot and resolve any issues.

I was introduced to Git and GitHub in May of 2014 – just shy of 10 years since Git was created in 2005. That same day I was also handed a MacBook Pro laptop and an IntelliJ license, the main tools with which I was to begin my new role as a developer in a new position at a new company. It all sounds lovely, right?

Imagine, you are developing Java software and suddenly you encounter an error? Where could you have possibly gone wrong? There are many types of errors that you will encounter while developing Java software, but most are avoidable. Some errors are minor lapses when writing codes but that is very much mendable. If you have an error monitoring tool such as Stackify Retrace, you can write codes with ease.

If you shudder thinking about compilation for different platforms, I know the feeling. One of the Java promises, the WORA (Write Once, Run Anywhere) principle, while revolutionizing platform independence, it stopped short of one more step – to be able to deploy anywhere. Personally, I think that WORADA sounds awesome, but I guess before Docker it didn’t occur to people that eliminating “works on my machine” is as simple as shipping your machine.

Troubleshooting issues in your applications can be a complicated task requiring visibility into various components. In the worst-case scenario, to understand what is happening and why it is happening you will need metrics, logs, and traces combined together. Having that information will give you the possibility to slice and dice the data and get to the root cause efficiently. In this article, we will focus on logs and how to configure logging for your Java applications.

Logging is a crucial part of the observability of your Java applications. Combined with metrics and traces gives full observability into the application behavior and is invaluable when troubleshooting. Logs, combined with metrics shortens the time needed to find the root cause and allows for quick and efficient resolutions of problems.