Abstract
Organizations worldwide are rapidly migrating their IT services and infrastructure to cloud data centers in order to reduce costs and guarantee high availability, scalability, and security. Considering that service downtime translates into major financial losses, new mechanisms need to be developed to assess the availability of cloud data center dynamically. However, data center availability analysis remains a complex task and one that is prone to human error due the large number of components and their interconnections. In this work we propose a methodology for acquiring information about a data center infrastructure and, automatically, generating computational models to assess its availability. We make use of the Redfish standard to acquire information about the data center infrastructure, the main standard for data center management. To demonstrate the applicability of our proposal, we conduct a study to analyze availability and failure costs of an application hosted in a cloud and we compare different scenarios with redundant servers according to the TIA-942 data center standard. Results show that a lower tier level with redundant servers, in some cases, is more suitable (more available and less costly) than higher tier levels without redundant servers hosting a cloud application.
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References
Araujo, J., Maciel, P., Torquato, M., Callou, G., Andrade, E.: Availability evaluation of digital library cloud services. In: 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 666–671. IEEE (2014)
Dantas, J., Matos, R., Araujo, J., Maciel, P.: Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud. Computing 97(11), 1121–1140 (2015)
Endo, P.T., Santos, G.L., Rosendo, D., Gomes, D.M., Moreira, A., Kelner, J., Sadok, D., Gonçalves, G.E., Mahloo, M.: Minimizing and managing cloud failures. Computer 50(11), 86–90 (2017)
Ferreira, J., Dantas, J., Araujo, J., Mendonca, D., Maciel, P., Callou, G.: An algorithm to optimize electrical flows of private cloud infrastructures. In: 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 771–776. IEEE (2015)
Gagnaire, M., Diaz, F., Coti, C., Cerin, C., Shiozaki, K., Xu, Y., Delort, P., Smets, J.P., Le Lous, J., Lubiarz, S., et al.: Downtime statistics of current cloud solutions. Technical report, International Working Group on Cloud Computing Resiliency (2014)
Gomes, D., Endo, P., Gonçalves, G., Rosendo, D., Santos, G., Kelner, J., Sadok, D., Mahloo, M.: Evaluating the cooling subsystem availability on a cloud data center. In: IEEE Symposium on Computers and Communications. IEEE (2017)
Gonçalves, G., Endo, P.T., Rodrigues, M., Kelner, J., Sadok, D., Curescu, C.: Risk-based model for availability estimation of SAF redundancy models. In: 2016 IEEE Symposium on Computers and Communication (ISCC), pp. 886–891. IEEE (2016)
Groote, J.F., Kouters, T.W., Osaiweran, A.: Specification guidelines to avoid the state space explosion problem. Softw. Test. Verif. Reliab. 25(1), 4–33 (2015)
Guo, C., Yuan, L., Xiang, D., Dang, Y., Huang, R., Maltz, D., Liu, Z., Wang, V., Pang, B., Chen, H., et al.: Pingmesh: a large-scale system for data center network latency measurement and analysis. In: ACM SIGCOMM Computer Communication Review, vol. 45, pp. 139–152. ACM (2015)
Heidari, P., Hormati, M., Toeroe, M., Al Ahmad, Y., Khendek, F.: Integrating open SAF high availability solution with open stack. In: 2015 IEEE World Congress on Services (SERVICES), pp. 229–236. IEEE (2015)
Hojati, E., Chen, Y., Sill, A.: Benchmarking automated hardware management technologies for modern data centers and cloud environments. In: Proceedings of the 10th International Conference on Utility and Cloud Computing, pp. 195–196. ACM (2017)
Jammal, M., Kanso, A., Heidari, P., Shami, A.: Evaluating high availability-aware deployments using stochastic Petri net model and cloud scoring selection tool. IEEE Trans. Serv. Comput. (2017)
Kumari, P., Saleem, F., Sill, A., Chen, Y.: Validation of redfish: the scalable platform management standard. In: Companion Proceedings of the 10th International Conference on Utility and Cloud Computing, pp. 113–117. ACM (2017)
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., Dantas, J.: 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), pp. 50–57. IEEE (2017)
Melo, C., Matos, R., Dantas, J., Maciel, P.: Capacity-oriented availability model for resources estimation on private cloud infrastructure. In: 2017 IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC), pp. 255–260. IEEE (2017)
Rocha, É., Endo, P.T., Leoni, G., Braga, J., Lynn, T.: Analyzing the impact of power infrastructure failures on cloud application availability. In: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1746–1751. IEEE (2017)
Rosendo, D., Santos, G., Gomes, D., Moreira, A., Gonçalves, G., Endo, P., Kelner, J., Sadok, D., Mahloo, M.: How to improve cloud services availability? Investigating the impact of power and it subsystems failures. In: HICSS Hawaii International Conference on System Sciences. HICSS (2017)
Santos, G., Endo, P., Gonçalves, G., Rosendo, D., Gomes, D., Kelner, J., Sadok, D., Mahloo, M.: Analyzing the it subsystem failure impact on availability of cloud services. In: IEEE Symposium on Computers and Communications. IEEE (2017)
Smith, W.E., Trivedi, K.S., Tomek, L.A., Ackaret, J.: Availability analysis of blade server systems. IBM Syst. J. 47(4), 621–640 (2008)
Sousa, E., Lins, F., Tavares, E., Cunha, P., Maciel, P.: A modeling approach for cloud infrastructure planning considering dependability and cost requirements. IEEE Trans. Syst. Man Cybern.: Syst. 45(4), 549–558 (2015)
Verma, A.K., Ajit, S., Karanki, D.R.: Reliability and Safety Engineering, vol. 43. Springer, London (2010)
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Santos, G.L. et al. (2020). A Methodology for Automating the Cloud Data Center Availability Assessment. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2019. Advances in Intelligent Systems and Computing, vol 926. Springer, Cham. https://doi.org/10.1007/978-3-030-15032-7_85
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DOI: https://doi.org/10.1007/978-3-030-15032-7_85
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