Planejamento de Arquiteturas Resilientes em Kubernetes: Uma abordagem baseada em Tempo de Recuperação e Consumo Elétrico
Resumo
A arquitetura de microsserviços tem sido cada vez mais utilizada para implantar sistemas na nuvem. No entanto, essas arquiteturas continuam sujeitas aos efeitos de desastres. Devido à quantidade de cenários e elementos de configuração possíveis, preparar sistemas de microsserviços para recuperação em um tempo restrito e sem grandes impactos no consumo elétrico é um desafio. Este artigo propõe um modelo capaz de quantificar o tempo de recuperação e o consumo elétrico deste tipo de sistema para auxiliar no planejamento de sistemas resilientes e ecologicamente conscientes. Os resultados do modelo identificaram os elementos mais significativos da arquitetura e delimitaram intervalos com maiores melhorias relativas.Referências
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Bhavsar, S., Agrawal, A., Ropalkar, T., Kamdi, P., Hajare, A., Deshpande, S., Rathi, R., and Garg, D. (2023). Kubernetes cluster disaster recovery using aws. In 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), pages 1–6. IEEE.
Gomes, C., Tavares, E., Junior, M. N. d. O., and Nogueira, B. (2022). Cloud storage availability and performance assessment: a study based on nosql dbms. The Journal of Supercomputing, 78(2):2819–2839.
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Isa, I. S. M., Musa, M. O., El-Gorashi, T. E., and Elmirghani, J. M. (2019). Energy efficient and resilient infrastructure for fog computing health monitoring applications. In 2019 21st International Conference on Transparent Optical Networks (ICTON), pages 1–5. IEEE.
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Longo, F., Ghosh, R., Naik, V. K., Rindos, A. J., and Trivedi, K. S. (2017). An approach for resiliency quantification of large scale systems. ACM SIGMETRICS Performance Evaluation Review, 44(4):37–48.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Maciel, P. R. M. (2023). Performance, reliability, and availability evaluation of computational systems, Volume 2: Reliability, availability modeling, measuring, and data analysis. CRC Press.
Nong, M., Huang, L., and Liu, M. (2022). Allocation of resources for cloud survivability in smart manufacturing. ACM Transactions on Management Information Systems (TMIS), 13(4):1–11.
Pinheiro, T., Oliveira, D., Matos, R., Silva, B., Pereira, P., Melo, C., Oliveira, F., Tavares, E., Dantas, J., and Maciel, P. (2021). The mercury environment: a modeling tool for performance and dependability evaluation. In Intelligent Environments 2021: Workshop Proceedings of the 17th International Conference on Intelligent Environments, volume 29, page 16. IOS Press.
Ramasamy, B., Na, Y., Kim, W., Chea, K., and Kim, J. (2022). Hacm: High availability control method in container-based microservice applications over multiple clusters. IEEE Access, 11:3461–3471.
Trivedi, K. S. and Xia, R. (2015). Quantification of system survivability. Telecommunication Systems, 60:451–470.
Wang, J. C. (2022). Understanding the energy consumption of information and communications equipment: A case study of schools in taiwan. Energy, 249:123701.
Welsh, T. and Benkhelifa, E. (2020). On resilience in cloud computing: A survey of techniques across the cloud domain. ACM Computing Surveys (CSUR), 53(3):1–36.
Bhavsar, S., Agrawal, A., Ropalkar, T., Kamdi, P., Hajare, A., Deshpande, S., Rathi, R., and Garg, D. (2023). Kubernetes cluster disaster recovery using aws. In 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), pages 1–6. IEEE.
Gomes, C., Tavares, E., Junior, M. N. d. O., and Nogueira, B. (2022). Cloud storage availability and performance assessment: a study based on nosql dbms. The Journal of Supercomputing, 78(2):2819–2839.
Hamadah, S. and Aqel, D. (2019). A proposed virtual private cloud-based disaster recovery strategy. In 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), pages 469–473. IEEE.
Isa, I. S. M., Musa, M. O., El-Gorashi, T. E., and Elmirghani, J. M. (2019). Energy efficient and resilient infrastructure for fog computing health monitoring applications. In 2019 21st International Conference on Transparent Optical Networks (ICTON), pages 1–5. IEEE.
Kubernetes (2023). Kubernetes production-grade container orchestration. [link]. Accessed: 2023-08-21.
Lin, W., Shi, F., Wu, W., Li, K., Wu, G., and Mohammed, A.-A. (2020). A taxonomy and survey of power models and power modeling for cloud servers. ACM Computing Surveys (CSUR), 53(5):1–41.
Longo, F., Ghosh, R., Naik, V. K., Rindos, A. J., and Trivedi, K. S. (2017). An approach for resiliency quantification of large scale systems. ACM SIGMETRICS Performance Evaluation Review, 44(4):37–48.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Maciel, P. R. M. (2023). Performance, reliability, and availability evaluation of computational systems, Volume 2: Reliability, availability modeling, measuring, and data analysis. CRC Press.
Nong, M., Huang, L., and Liu, M. (2022). Allocation of resources for cloud survivability in smart manufacturing. ACM Transactions on Management Information Systems (TMIS), 13(4):1–11.
Pinheiro, T., Oliveira, D., Matos, R., Silva, B., Pereira, P., Melo, C., Oliveira, F., Tavares, E., Dantas, J., and Maciel, P. (2021). The mercury environment: a modeling tool for performance and dependability evaluation. In Intelligent Environments 2021: Workshop Proceedings of the 17th International Conference on Intelligent Environments, volume 29, page 16. IOS Press.
Ramasamy, B., Na, Y., Kim, W., Chea, K., and Kim, J. (2022). Hacm: High availability control method in container-based microservice applications over multiple clusters. IEEE Access, 11:3461–3471.
Trivedi, K. S. and Xia, R. (2015). Quantification of system survivability. Telecommunication Systems, 60:451–470.
Wang, J. C. (2022). Understanding the energy consumption of information and communications equipment: A case study of schools in taiwan. Energy, 249:123701.
Welsh, T. and Benkhelifa, E. (2020). On resilience in cloud computing: A survey of techniques across the cloud domain. ACM Computing Surveys (CSUR), 53(3):1–36.
Publicado
21/07/2024
Como Citar
FÉ, Iure; SILVA, Luis Guilherme; SOARES, André; REGO, Paulo; SILVA, Francisco Airton.
Planejamento de Arquiteturas Resilientes em Kubernetes: Uma abordagem baseada em Tempo de Recuperação e Consumo Elétrico. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 51. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 228-239.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2024.2997.
