Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper we formalize these practices and show that automated deployment — proven undecidable in the general case — is algorithmically treatable for microservices. Our key assumption is that the configuration life-cycle of a microservice is split into two phases: (i) creation, which entails establishing initial connections with already available microservices, and (ii) subsequent binding/unbinding with other microservices. To illustrate the applicability of our approach, we implement an automatic optimal deployment tool and compute deployment plans for a realistic microservice architecture, modeled in the Abstract Behavioral Specification (ABS) language.

Optimal and automated deployment for microservices

Bravetti, Mario;Giallorenzo, Saverio;Talevi, Iacopo;Zavattaro, Gianluigi
2019

Abstract

Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper we formalize these practices and show that automated deployment — proven undecidable in the general case — is algorithmically treatable for microservices. Our key assumption is that the configuration life-cycle of a microservice is split into two phases: (i) creation, which entails establishing initial connections with already available microservices, and (ii) subsequent binding/unbinding with other microservices. To illustrate the applicability of our approach, we implement an automatic optimal deployment tool and compute deployment plans for a realistic microservice architecture, modeled in the Abstract Behavioral Specification (ABS) language.
2019
Fundamental Approaches to Software Engineering, FASE 2019.
351
368
Bravetti, Mario; Giallorenzo, Saverio*; Mauro, Jacopo; Talevi, Iacopo; Zavattaro, Gianluigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/686792
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