This attachment contains documents on strategies for detecting antipatterns using dynamic analysis, based on logs extracted from sidecars in a Kubernetes environment hosting the Spinnaker (https://spinnaker.io/) application. These antipatterns were selected through a systematic literature review to identify the most critical antipatterns and evaluate their detection strategies. The emphasis was on antipatterns that either lacked effective detection by current methods or were not well addressed by static analysis techniques (e.g., source code, repositories, or process artifacts). All processes related to the detection and triggering of Spinnaker tools, which aim to generate concise logs of Istio usage within a Kubernetes cluster, were included to facilitate understanding of the main idea behind the detections. In addition, we have gathered information on how to execute, manage, and access the log data produced by Istio sidecars deployed with the Spinnaker application. This includes configuring the sidecars to properly capture logs, adjusting log levels, and ensuring that telemetry collection is working as intended. More details are available in the text documents in the files. The file "spinnaker-artifacts-20250524T182034Z-1-001.zip" contains information on detections, strategies, decisions, and results based on antipatterns, derived from Spinnaker logs. On the other hand, the file "runtime-detection-notebook-artifacts-20250524T182033Z-1-001.zip" displays instructions for executing, collecting, and orchestrating Spinnaker, as well as for gathering and processing its logs. Additionally, there is a dataset of logs available for three types of executions: - Initial (toy example), - Intermediate (with a small "hello world" flow inside Spinnaker), and - Complete (focused on achieving more functionalities). References: - [1] L. H. de Braz, B. B. N. de França, and B. B. P. Cafeo, “Dynamic Analysis for Detecting Microservices Antipatterns,” Anais do XIX Simpósio Brasileiro de Componentes, Arquiteturas e Reutilização de Software (SBCARS 2025). Sociedade Brasileira de Computação, pp. 67–78, Sep. 22, 2025. doi: 10.5753/sbcars.2025.14576. - [2] L. H. de Braz, "Microservice Antipatterns: an approach for detection using dynamic analysis", Computer Science Dissertation. Dec. 04, 2025.