Software rarely comes without maintenance after it is released. There can be bugs not captured in development or performance that might not meet expectations; therefore, it is crucial to be able to collect data from running software, preemptively addressing such issues. A common way to monitor the general health of a system is by monitoring it through the users' perspective — so-called "black-box" monitoring. Making a more sophisticated analysis of software requires code that offers no functionality to the software, whose purpose is to create data about the software itself. A common way of creating such data is through logging. While logging can be used in the general case, alternatively, more specific solutions can offer an easier pipeline to work with; while not being suited for tasks such as root-cause analysis.This study briefly looks at four different frameworks, all having different approaches to collect and structure data. This study also covers the development of a proof-of-concept framework that creates structured events through logging — along with a SQL-server database to store the event data.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-166919 |
| Date | January 2020 |
| Creators | Persson, Edvin |
| Publisher | Linköpings universitet, Programvara och system |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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