Building More Sophisticated Issue Tracking in an ELK Environment Part 1 - Laying the Foundation for Issue Tracking

Instead of manually searching through logs to analyze the cause when an issue occurs, it's important to secure visibility into log data by leveraging the ELK stack. Storing logs in ElasticSearch and visualizing the data through a Kibana dashboard enables more agile responses.

You can implement a RequestLoggingFilter to intercept and log the client's request and the server's response data. Here, using ContentCachingWrapper allows the data to be read again even after the Body Stream has been read, enabling logging without any loss of information.

The log data is structured through the RequestLog class to include detailed information such as request URL, method, headers, body, response status code, and elapsed time. This lays the foundation for quickly grasping the necessary context when an issue occurs.