Microservices are getting commonplace, since they enable obtaining cloud-native applications. Ensuring that applications adhere to microservices' design principles is crucial for microservices to deliver their promises. This includes resolving architectural smells possibly denoting violations of such principles. To this end, we propose μKuRE, a tool for resolving architectural smells in Kubernetes-deployed microservices applications. μKuRE takes as input an application specification in μTOSCA, a microservice-oriented profile of the OASIS standard TOSCA, and the manifest files specifying the application deployment in Kubernetes. μKuRE then automatically detects architectural smells for microservices, and it refactors both the application specification and its deployment to automatically resolve the detected smells.
Soldani, J., Rendina, D., Fontana, F., Brogi, A. (2023). Kubernetes-Enabled Detection and Resolution of Architectural Smells for Microservices. In Proceedings - 17th IEEE International Conference on Service-Oriented System Engineering, SOSE 2023 (pp.75-80). IEEE [10.1109/SOSE58276.2023.00015].
Kubernetes-Enabled Detection and Resolution of Architectural Smells for Microservices
Rendina, Davide;Fontana, Francesca Arcelli
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2023
Abstract
Microservices are getting commonplace, since they enable obtaining cloud-native applications. Ensuring that applications adhere to microservices' design principles is crucial for microservices to deliver their promises. This includes resolving architectural smells possibly denoting violations of such principles. To this end, we propose μKuRE, a tool for resolving architectural smells in Kubernetes-deployed microservices applications. μKuRE takes as input an application specification in μTOSCA, a microservice-oriented profile of the OASIS standard TOSCA, and the manifest files specifying the application deployment in Kubernetes. μKuRE then automatically detects architectural smells for microservices, and it refactors both the application specification and its deployment to automatically resolve the detected smells.
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