Director: a cloud microservice selection framework

• Ano de defesa: 2019
• Autor(a) principal: Costa, Marcelo de França
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Engenharia de Sistemas e Computação; UFRJ
• Palavras-chave em Português: Software ecosystems; Software architecture; Cloud computing; Cognitive computing; Microservices; Software engineering; CNPQ::ENGENHARIAS
• Link de acesso: http://hdl.handle.net/11422/14062

[EN] The Software Ecosystem research field has been receiving an increasing amount of attention from both academia and industry, as many organizations have been adopting them as a collaborative platform to achieve innovation faster than before. More recently, with the advent of Cloud Computing, modern ecosystems have been offered as a service, allowing actors to contribute, but also commercialize their own solutions, by reusing available software assets, popularly in the shape of microservices, i.e., very specific functionality, usually exposed through Web technologies. With the current proliferation of platforms and microservices, an open and relevant challenge for software architects is to find and acquire the most adequate component, given a set of requirements and priorities. In this context, we propose DIRECTOR: A cloud microservice selection framework, based on complementary technical, social and semantical perspectives, i.e., by relying on objective analysis, reputation and artificial intelligence, respectively. The results obtained through a proof-of-concept (PoC), and a feasibility study conducted with industry experts, indicate that it can support software acquisition via discovery, evaluation and comparison of microservices, being able to recommend the fittest among hundreds of candidates in multiple cloud platforms.