Towards Logging Noisiness Theory: quality aspects to characterize unwanted log entries
Abstract
Context: Logging tasks track the system's functioning by keeping records of evidence that have been analyzed by monitoring and observability activities. For these activities to be effective, it is necessary to consider the quality of the consumed information. Problem: However, the presence of noise - unwanted information - compromises the log files' quality. The noisiness of a log file can be affected among other things by: (i) the wrong severity log choices, (ii) the production of duplicate entries, (iii) the incompleteness of the information, (iv) the inappropriate format of the entries, (v) the amount of information generated. Objective: This work aims to broadly define the concept of noise in the context of logging, proposing the initial steps of Logging Noisiness, a theory on quality aspects to characterize unwanted log entries.
Cite
@article{arxiv.2106.03018,
title = {Towards Logging Noisiness Theory: quality aspects to characterize unwanted log entries},
author = {Eduardo Mendes and Fabio Petrillo},
journal= {arXiv preprint arXiv:2106.03018},
year = {2021}
}
Comments
6 pages