A structured approach to selecting the most suitable log management system for an organization

With the advent of digitalization, a typical organization today will contain an ecosystem of servers, databases, and other components. These systems can produce large volumes of log data on a daily basis. By using a log management system (LMS) for collecting, structuring and analyzing these log events, an organization could benefit in their services. The primary intent with this thesis is to construct a decision model that will aid organizations in finding a LMS that most fit their needs. To construct such a model, a number of log management products are investigated that are both proprietary and open source. Furthermore, good practices of handling log data are investigated by reading various papers and books on the subject. The result is a decision model that can be used by an organization for preparing, implementing, maintaining and choosing a LMS. The decision model makes an attempt to quantify various properties such as product features, but the LMSs it suggests should mostly be seen as a decision basis. In order to make the decision model more comprehensive and usable, more products should be included in the model and other factors that could play a part in finding a suitable LMS should be investigated.