Elasticsearch logging – log and search

Machine data, WiFi data, computer data, it doesn't matter, we log everything!

Pure Data provides a Basic Elasticsearch logging solution. The amount of log data increases exponentially. Whether this is data from industrial machines, PLCs, computers or software applications. On the one hand, you want to keep log data to a limited extent, storage is often expensive and complex. On the other hand, you want to keep as much log data as possible in order to be able to do analyzes and discover trends based on the historically collected.

Log data features

Log data has a number of specific characteristics. A log line consists of a timestamp (date and time) and an event. This event represents an event. This can, for example, be an error code that occurred at a specific moment (the timestamp), or, for example, a location of a vehicle or a person.

Basic Elasticsearch logging solution

The solution that Pure Data provides provides a solution to the problems related to the storage of logging. Many different types of log data can be stored in 1 solution in a simple way and they can also be searched at lightning speed. In addition to saving the log data, the solution can also directly create visualizations from which trends can easily be extracted. Machine-learning algorithms to be implemented, if necessary, ensure that the checking of the logs is automated. The solution is extremely scalable and can be expanded to an environment in which billions of log lines and Terrabytes of data can be loaded. The big advantage of this is that the initial costs can be kept low. Costs grow with consumption. Depending on the environment, the implementation time is only a few days.

Whitepaper "From Hype to Practice"

Would you like more information about the logging solution and how it can be used for your organization? Please fill in the form below or contact us by phone. In our white paper “From Hype to Practice” you will find some examples of an Elasticsearch logging solution that we have implemented.

Download the white paper