Many things in programming sound like they should be easy, but are quite hard. Calculating elapsed time in Java is one of those. How hard could that be? As it turns out, it can be tricky. For starters, we have the fact that time itself is a tricky concept. For a quick example, remember that many places around the world observe Daylight Savings Time. Failing to take DST into account when you should, can and often does result in incorrect calculations.
The Apache Tomcat software is an open-source implementation of the ava Servlet, JavaServer Pages (JSPs), Java Expression Language and Java WebSocket technologies. Tomcat is often used as a backend application server that connects to other web-facing servers like Apache and Microsoft IIS. Tomcat also includes its own native HTTP connector that allows it to be used as a standalone HTTP server.
When it comes to Java applications, to make sure they run at peak performance, it’s critical to close the resource gap between the code and the virtual machine it’s running on – if there is one. The way to do that is by peaking into and fine-tuning the Java Virtual Machine (JVM). However, that’s easier said than done. Many factors can influence JVM performance, and during tuning, you must consider all of them. Though, there are ways around that to make it not be such a pain.
The Java Virtual Machine (JVM) dynamically manages memory for your applications, ensuring that you don’t need to manually allocate and release memory in your code. But anyone who’s ever encountered a java.lang.OutOfMemoryError exception knows that this process can be imperfect—your application could require more memory than the JVM is able to allocate.
Managing an application’s performance, and specifically keeping it in good condition, is one of the hardest challenges in software development. That’s true for virtually any programming language and platform. Java is no exception to this rule. But beyond that, Java also presents some unique challenges of its own.
Equality is an essential concept when programming, not only in Java but in pretty much all programming languages. After all, much of what we do when writing code has to do with comparing values and then making decisions based on the results of such comparisons.
Exception handling in Java isn’t an easy topic. Beginners find it hard to understand and even experienced developers can spend hours discussing how and which Java exceptions should be thrown or handled. That’s why most development teams have their own set of rules on how to use them.
It’s one thing to write code that works. But what about clean, readable, concise code? That’s another thing entirely. To create an app that solves one problem? Not that hard. What about one that not only solves the problem, but it’s also easy and pleasurable to use? Now we’re talking. You could apply the same reasoning for many software properties, which would make for a long article. Instead, let’s focus on only one of those properties: performance.
If you have deployed a Java application in production, you’ve probably encountered a situation where the application suddenly starts to take up a large amount of CPU. When this happens, application response becomes sluggish and users begin to complain about slow response. Often the solution to this problem is to restart the application and, lo and behold, the problem goes away – only to reappear a few days later.
Whether you’re investigating memory leaks or debugging errors, Java Virtual Machine (JVM) runtime metrics provide detailed context for troubleshooting application performance issues. For example, if you see a spike in application latency, correlating request traces with Java runtime metrics can help you determine if the bottleneck is the JVM (e.g., inefficient garbage collection) or a code-level issue.
