It looks at the structure of your system and how its components are interconnected by tracing transactions across distributed applications. You can track active threads in real time, see request count and response patterns, as well as JVM performance metrics such as CPU and memory usage, garbage collection, and JVM arguments.
Stagemonitor is a community-developed monitoring tool designed for clustered application stacks. That means that you can use it to monitor development, testing, and production of JVM-based applications running on multiple servers while keeping a low overhead.
With Stagemonitor, you can view historical or live data from the cluster or the developer server, create custom alerts, and set thresholds for each JVM metric. It also allows you to create custom dashboards to visualize and analyze metrics. MoSKito is a complete toolset for DevOps to monitor the performance and behavior of Java applications.
It collects, analyzes, and stores all critical JVM performance metrics such as memory, CPU, threads, caches, load distribution, and many more in real time. You can set thresholds and notification alerts, record user activity, and provide a clean dashboard to monitor all application processes in multi-node production environments. RUM looks at how your visitors interact with your application, giving you visibility into its dependencies by showing asset download and page render time.
Sematext Experience is a real user monitoring tool that allows you to track app performance and receive alerts whenever it detects anomalies that affect end-user experience.
You can correlate the end-user behavior metrics provided by the Sematext Experience with the metrics provided by Sematext Java Monitoring to expand your view over a given period. This offers you a broader perspective when troubleshooting or looking into the metrics in real-time. Knowing how your users interact with your application offers you a unique opportunity to get to the root cause of the potential issue faster and more efficiently by looking into the problem from various angles.
If you want to see how Sematext Experience stacks against similar solutions, read our article about the best real user monitoring tools available today. Java logs provide useful insight into executed code, errors, potential issues, and many more. By aggregating access logs, you can detect the most popular, fastest, as well as slowest endpoints. Analyzing logs using the command line may take time, and doing that on multiple servers may be problematic.
Instead, you can use log analyzers that do the hard work for you. Otherwise, for staging and production environments, you should turn to a hosted logging solution, such as Sematext Logs. Sematext Logs is a logging service that allows you to centralize logs from various sources like applications, microservices, operating systems, different devices, and, of course, Java-based applications.
The platform enables you to structure, visualize and analyze all collected data passively and actively. You can create informative dashboards connecting every piece of information and observe how your systems behave in real-time or set up alerts to be notified when a critical event happens. Use per-user access restrictions to control who can access which data and store your data in the S3-compatible storage for no additional cost.
For more details on how Sematext Logs stacks against similar platforms, we compared it with solutions from the entire log management landscape, from log analysis software and log aggregation tools to log management solutions and cloud-based logging services. This is why you should look for an integrated monitoring tool that allows you to correlate logs, metrics, and real user monitoring data — such as Sematext Cloud.
Sematext Cloud is an observability platform providing you a rich set of features. By helping you follow the flow of a request, you can see what types of method calls are responsible for your response time. Designed for the development cycle only. Application performance management APM tools take on the task of tracking all requests on a production system. The trick with these profilers is to provide the right information in a smart way so as not to impact production performance.
This is done by aggregating timing statistics and sampling traces. This gives you method level visibility to your code that is running in production.
The ability to monitor your most critical environment: Production. Debug production live by analyzing traces and exceptions. Aggregate summaries to see highly used requests to help focus development time. Some tools lack support for async queries or are not tuned properly and slow down your application.
Note: Some providers, including Stackify Retrace , provide free trials that can be used to help identify immediate problems. Some APM products include this as an additional feature. There are also standalone products, such as Google PageSpeed. The JVM provides a great deal of valuable information such as garbage collection, memory usage, and thread counts.
This data is made available via JMX. Stackify Retrace provides JVM metric monitoring via App Monitors and automatically applies smart defaults based on the type of application discovered. Can be difficult to connect to in a staging and production environment. Aggregation and comparing data might be time-consuming.
It seems a trivial feature, but it comes in handy in the later stage of the analysis. The combination of XRebel and JRebel may be the best java profiler tools available. XRebel allows java developers to check the application performance from end to end to discover if there any performance issues present during the development phase. If any changes are required, JRebel allows the java developers to skip the redeploy process and preview the changes instantly, which enables the developer to quickly evaluate using XRebel that whether or not the difference provides the desired performance impact or not.
The best feature from XRebel is saving significant time consumed during redeploys; it can result in getting efficient performance improvements way faster than any other profilers.
It is also effortless to include the XRebel profiler in your web application. To have the profiler in your web application, just a single VM argument is required to be passed, and right after that, a small icon can be seen at the bottom left of every page that can be clicked to view the XRebel interface.
XRebel offers a two weeks long Free trial version. NetBeans is mainly known as an excellent debugger, but to our surprise, it is also regarded as one of the best java profilers. It is also a good choice for lightweight development and profiling. Having the functionality of both means that along with offering the functionality of a profiler with features like monitoring code execution time taken by the CPU, details of the run-time behavior of code, and creation of objects. Netbeans profiler also increases the operating speed of the application, which results in efficient memory usage.
The best part is that it is free to use and can be downloaded from their website. While It resembles a lot with Java VisualVM in terms of features, and both are also free, what gives Netbeans a lead is that it provides everything bundled in one program with IDE.
JIP is a fully Java-coded, light-weighted profiler designed for effective profiling. It has a series of promising java profiler tools along with the ON and OFF features to filter out multiple measurements at runtime. It can be run on any platform that supports Java. Filtering options by class or packages, efficient memory management, and easier debugging are some other useful features offered by JIP.
It is an open-source profiler, making it even more popular among Java developers as it is free of cost, and developers can contribute to its further improvement. Stackify Prefix is another great java profiler with some unique profiling tools.
It provides a feature to display details about every web request so you can monitor every single step of what your java web app is doing and the time it is taking for it. But in general, I recommend starting at the top and begin work on the most significant performance problem first. That will provide you with the biggest performance improvement, and you might not need to fix more than a few of these issues to fulfill your performance requirements.
Enough about general performance tuning tips. There are lots of different options to concatenate String s in Java. The answer depends on the code that concatenates the String.
But please keep in mind, that the StringBuilder , in contrast to StringBuffer , is not thread-safe and might not be a good fit for all use cases.
You just need to instantiate a new StringBuilder and call the append method to add a new part to the String. The following code snippet shows a simple example. During each iteration, this loop converts i into a String and adds it together with a space to the StringBuilder sb.
As you can see in the code snippet, you can provide the first element of your String to the constructor method. That will create a new StringBuilder containing the provided String and a capacity for 16 additional characters. If you already know how many characters your String will contain, you can provide that number to different constructor method to instantiate a StringBuilder with the defined capacity.
String s are immutable, and the result of each String concatenation is stored in a new String object. Your Java compiler will optimize this and perform the concatenation at compile time. So, at runtime, your code will just use 1 String , and no concatenation will be required. Another quick and easy way to avoid any overhead and improve the performance of your application is to use primitive types instead of their wrapper classes.
That allows your JVM to store the value in the stack instead of the heap to reduce memory consumption and overall handle it more efficiently.
Especially the latter one is popular because of its precision. But that comes at a price. BigInteger and BigDecimal require much more memory than a simple long or double and slow down all calculations dramatically.
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