When it comes to troubleshooting application performance, metrics are no longer enough. To fully understand the environment you need logs and traces. Today, we’re going to focus on your Java applications.

Logging in Java could be done just by easily writing data to a file, however, this is not the simplest or most convenient way of logging. There are frameworks for Java that provide the object, methods, and unified configuration methods that help setting up logging, store logs, and in some cases even ship them to a log centralization solution. On top of that, there are also abstraction layers that…

Having visibility into your Java application is crucial for understanding how it works right now, how it worked some time in the past and increasing your understanding of how it might work in the future. More often than not, analyzing logs is the fastest way to detect what went wrong, thus making logging in Java critical to ensuring the performance and health of your app, as well as minimizing and reducing any downtime. Having a centralized logging and monitoring solution helps reduce the Mean Time To Repair by improving the effectiveness of your Ops or DevOps team.

By following logging…

When providing services to your customers you need to keep an eye on everything that could impact your success with that — from low-level performance metrics to high-level business key performance indicators. From server-side logs to stack traces giving you full visibility into business and software processes that underpin your product. That’s where cloud monitoring tools and services come into play. They help you achieve full readiness of your infrastructure, applications, and make sure that your users and customers can use your platform to its full potential.

What Is Cloud Monitoring?

Cloud monitoring is a process of gaining observability into your cloud-based infrastructure, services…

Apache Solr was always ready to be extended. What was only needed is a binary with the code and the modification of the Solr configuration file, the solrconfig.xml and we were ready. It was even simpler with the Solr APIs that allowed us to create various configuration elements — for example, request handlers. What’s more, the default Solr distribution came with a few plugins already — for example, the Data Import Handler or Learning to Rank.

As consultants working with clients across different industries, dealing with a wide variety of use cases with Solr clusters monitored by Sematext Cloud the…

Working with Java applications has a lot of benefits. Especially when compared to languages like C/C++. In the majority of cases, you get interoperability between operating systems and various environments. You can move your applications from server to server, from operating system to operating system, without major effort or in rare cases with minor changes.

In this tutorial, we will talk about how different Java Garbage Collectors work and what you can expect from them. This will give us the necessary background to start tuning the garbage collection algorithm of your choice.

Before going into Java Garbage Collection tuning we need to understand two things. First of all, how garbage collection works in theory and how it works in the system we are going to tune. Our system’s garbage collector work is described by garbage collector logs and metrics from observability tools like Sematext Cloud for JVM. …

When working with Java or any other JVM-based programming language we get certain functionalities for free. One of those functionalities is clearing the memory. If you’ve ever used languages like C/C++ you probably remember functions like malloc, calloc, realloc and free. We needed to take care of the assignment of each byte in memory and take care of releasing the assigned memory when it was no longer needed. Without that, we were soon running into a shortage of memory leading to instability and crashes.

With Java, we don’t have to worry about releasing the memory that was assigned to an…

Through the lifetime of Solr we were given the possibility to work with cores, then collections and finally aliases — the alternative names for collections. Aliases allow the user to give your collection a new, virtual name and group multiple collections under that single virtual name. This allows isolation of the real collection name from the name that the client application is using. That allows changing the collection in the background without the need of bringing down the whole cluster and make your application or product unavailable. In Solr we have the option to use two aliases groups:

• standard aliases…