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Instrumenting Python with Kieker.
Simonov, Serafim, Düllmann, Thomas, Jung, Reiner and Gundlach, Sven (2023) Instrumenting Python with Kieker. Softwaretechnik-Trends, 43 (1). pp. 26-28.
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Abstract
Python has become a widely used programming language in big data, machine learning, and scientific modeling. In all these domains, performance is a key factor to success and requires the ability to understand the runtime behavior of software. Therefore, we ported Kieker monitoring to Python and evaluated different approaches to introduce probes into code.
In this paper, we evaluate these approaches, show their benefits and limitations and provide a performance evaluation of the Kieker 4 Python framework.
Document Type: | Article |
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Funder compliance: | DFG:425916241 |
Additional Information: | 13th Symposium on Software Performance |
Keywords: | Runtime Observation. Application Monitoring, Python |
Research affiliation: | Kiel University > Software Engineering |
Refereed: | Yes |
Open Access Journal?: | Yes |
Publisher: | Gesellschaft für Informatik e.V. |
Date Deposited: | 21 Nov 2022 12:08 |
Last Modified: | 25 Apr 2024 14:58 |
URI: | https://oceanrep.geomar.de/id/eprint/57358 |
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