Top Trending Java Anomaly Detection Tools to Know Application failures occur due to a wide array of reasons, and there are several tools available to address possible sources for errors including log management tools, error trackers, and performance monitoring solutions. In this blog, we’ve researched and found the different ways to solve Java application errors and how tools can assist in identifying errors. The data that these tools collect is often comprise of unnecessary elements. How to know its relevance? That’s where anomaly detection tools come into picture. These tools have so much importance for the Java Application Development Company to attain desired results for the business. In the following post we’ll focus on detecting and predicting when anomalies happen. Let’s check them out.
1. X-Pack X-Pack is basically an extension to the ELK Stack that uses algorithms to help users know the behavior of their logs, identifying when they’re not working as desired. The package depends on logs as its data source, allowing the users to know how specific metrics have its impact on the application and how users experience it. Features: • Finding anomalies inside Elasticsearch log data as well as metrics.