Detecção de Overbooking em Aplicações Baseadas em Docker Através de Aprendizagem de Máquina

  • Pedro Horchulhack PUCPR
  • Eduardo Viegas PUCPR
  • Altair Santin PUCPR
  • Felipe Ramos PUCPR

Resumo


O artigo propõe um modelo de aprendizado de máquina para detectar ambientes Kubernetes com overbook de recursos em um contêiner do Docker. As métricas do aplicativo e do sistema foram coletadas continuamente, as quais foram usadas como entrada para o modelo para identificar interferência causada por multi-tenancy. Os experimentos foram executados em um cluster Kubernetes, com um aplicativo de Big Data baseado em contêiner, o que mostrou que o modelo pode detectar overbooking de recursos com precisões de até 98% em um cenário que pode causar degradação no desempenho do aplicativo, com taxas de overbooking de até 1,2.

Referências

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Publicado
23/05/2022
HORCHULHACK, Pedro; VIEGAS, Eduardo; SANTIN, Altair; RAMOS, Felipe. Detecção de Overbooking em Aplicações Baseadas em Docker Através de Aprendizagem de Máquina. In: WORKSHOP DE TRABALHOS DE INICIAÇÃO CIENTÍFICA E DE GRADUAÇÃO - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 40. , 2022, Fortaleza/CE. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 209-216. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc_estendido.2022.223437.