Application failures are an inevitable part of their development. Every developer has faced some errors that crop up as we move ahead. But wouldn’t it be better if we the anomalies detected in real-time and you warned? Even better, if you could find out what went wrong and where? Fortunately, Java developers India has quite a few anomaly tools that can help course correct in time. Here is our top five:
An extension of Elastic Stack, X-Pack is essentially a security feature. It works by monitoring logs for information. It monitors, alerts and reports on the behavior of the logs. It uses machine learning algorithms to monitor log behavior and flagging any unusual behavior. The X-Pack also has graph capabilities, using metrics to illustrate user behavior.
It creates a basic behavior pattern by studying data from Elasticsearch logs. The logs are, in turn, culled from servers and applications. The data shows us trends and usage patterns. Any deviation from the pattern helps it predict the onset of a problem.
X-Pac is also incredibly easy to install. With Elasticsearch 5.0.0, whenever you install X-Pack, you automatically gain access Watcher, Marvel, and Shieldplugins. Moreover, you also do not have to worry about the plugin version, since it now comes with the X-Pac. With a default detection feature, X-Pac has also tightened user authority. Keep in mind that X-Pac is essentially an ELK tool and is well-integrated in its architecture. However, it is not as effective if you are out of ELK.
Powered by AI, Loom Systems use log analysis to compare and predict issues that can crop up in the development of an application. It automatically takes logs from applications and breaks it down according to different fields. The parsing of any streamed log is automatic. The AI function then compares the events between different applications, exposing any issues and helping in the prediction of anomalies.
The data examined according to the field type. The advantage of Loom Systems is its usage of AI to pinpoint the root cause in real time, allowing you to take corrective action in time. It uses the organizational database to explain the anomaly and provide you with recommended solutions. The Loom also ensures that the baseline remains dynamic, changing as the standard user behavior changes.
The Loom system has many positives – its dynamic baseline that evolves with time, a superior analytic component that exposes flaws and makes us understand why it occurred and its ability to provide you with an effective solution.
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So far we have only seen tools that detect errors in the log. But what you need is the source of the error and what caused it. The answer lies in OverOps. Instead of logs, it focuses on the source code and the variable state that causes the error.
The OverOps scores because it is the only tool that focuses on the code. It detects when and where code breaks during the production process. Thus, it gives us a complete picture of the anomaly, helping us to pinpoint the instance it occurred in the code deployment.
It is also pretty easy to install, taking no time in SaaS, Hybrid, and On-premises. It can be hosted on SaaS application, or deployed on-premises. You may even choose it simply for its uber cool dashboard. It works with StatsD compliant tools for visualization of anomaly detection.
Working with the JVM, OverOps extracts data from the applications. It compares the variable state with the JVM metrics, showing application errors. OverOps also has a collaborative add-on, providing links for errors in the logs as well. The link takes you to the very cause of the error with the source code.
Coralogix uses AI to show segregate the logs into patterns and show their flow, giving us an insight in real-time. While mapping the production flow, Coralogix can instantly detect the moment an issue occurs, giving us a precise insight.
By showing the original pattern in the log data, it also helps in the analysis of Big Data. It works on the assumption that most logs show similar patterns. The process brings out the big anomalies and not every small issue.
Anodot uses AI to uncover blind spots. It uses patented machine learning algorithms to deliver BI. The company boasts of revolutionary BI that uses your metrics and applies machine learning to analyze the data. Anomalies are detected instantly, and an alert is triggered.Tags: hire java developers india, Java developers, java programmers