This paper introduces RAMSES, an exemplar tailored for both practitioners and researchers working on self-adaptive microservice applications. By emphasizing a clear separation of concerns between the application and its adaptation logic, RAMSES realizes a reusable autonomic manager that implements a MAPE-K feedback loop whose components are microservices themselves. Its primary focus lies in addressing user-defined QoS attributes at runtime, like availability and performance. To illustrate its usage, we provide a practical example showing its mechanics in an e-food microservice application. Initial experiments indicate the advantages of utilizing RAMSES, as shown by a comparative analysis of the quality properties of a microservice application with and without self-adaptation.

(2024). RAMSES: An Artifact Exemplar for Engineering Self-Adaptive Microservice Applications . Retrieved from https://hdl.handle.net/10446/286569

RAMSES: An Artifact Exemplar for Engineering Self-Adaptive Microservice Applications

Scandurra, Patrizia
2024-01-01

Abstract

This paper introduces RAMSES, an exemplar tailored for both practitioners and researchers working on self-adaptive microservice applications. By emphasizing a clear separation of concerns between the application and its adaptation logic, RAMSES realizes a reusable autonomic manager that implements a MAPE-K feedback loop whose components are microservices themselves. Its primary focus lies in addressing user-defined QoS attributes at runtime, like availability and performance. To illustrate its usage, we provide a practical example showing its mechanics in an e-food microservice application. Initial experiments indicate the advantages of utilizing RAMSES, as shown by a comparative analysis of the quality properties of a microservice application with and without self-adaptation.
2024
Riccio, Vincenzo; Sorrentino, Giancarlo; Zamponi, Ettore; Camilli, Matteo; Mirandola, Raffaela; Scandurra, Patrizia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/286569
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