Making Runtime Data Useful for Incident Diagnosis: An Experience Report
Lautenschlager F, Ciolkowski M (2018)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2018
Publisher: Springer International Publishing
City/Town: Cham
Pages Range: 422-430
Conference Proceedings Title: Proceedings of the International Conference on Product-Focused Software Process Improvement (PROFES 2018)
Event location: Wolfsburg
ISBN: 978-3-030-03672-0
URI: https://link.springer.com/chapter/10.1007/978-3-030-03673-7_33
DOI: 10.1007/978-3-030-03673-7_33
Abstract
Important and critical aspects of technical debt often surface at runtime only and are difficult to measure statically. This is a particular challenge for cloud applications because of their highly distributed nature. Fortunately, mature frameworks for collecting runtime data exist but need to be integrated.
In this paper, we report an experience from a project that implements a cloud application within Kubernetes on Azure. To analyze the runtime data of this software system, we instrumented our services with Zipkin for distributed tracing; with Prometheus and Grafana for analyzing metrics; and with fluentd, Elasticsearch and Kibana for collecting, storing and exploring log files. However, project team members did not utilize these runtime data until we created a unified and simple access using a chat bot.
We argue that even though your project collects runtime data, this is not sufficient to guarantee its usage: In order to be useful, a simple, unified access to different data sources is required that should be integrated into tools that are commonly used by team members.
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How to cite
APA:
Lautenschlager, F., & Ciolkowski, M. (2018). Making Runtime Data Useful for Incident Diagnosis: An Experience Report. In Kuhrmann, Marco; Schneider, Kurt; Pfahl, Dietmar; Amasaki, Sousuke; Ciolkowski, Marcus; Hebig, Regina; Tell, Paolo; Klünder, Jil; Küpper, Steffen (Eds.), Proceedings of the International Conference on Product-Focused Software Process Improvement (PROFES 2018) (pp. 422-430). Wolfsburg, DE: Cham: Springer International Publishing.
MLA:
Lautenschlager, Florian, and Marcus Ciolkowski. "Making Runtime Data Useful for Incident Diagnosis: An Experience Report." Proceedings of the International Conference on Product-Focused Software Process Improvement (PROFES 2018), Wolfsburg Ed. Kuhrmann, Marco; Schneider, Kurt; Pfahl, Dietmar; Amasaki, Sousuke; Ciolkowski, Marcus; Hebig, Regina; Tell, Paolo; Klünder, Jil; Küpper, Steffen, Cham: Springer International Publishing, 2018. 422-430.
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