Multilevel Observability in Cloud Orchestration

Raquel Frizera Vassallo; Alexandre Pereira do Carmo; Felippe M.  de Queiroz; Anilton S. Garcia; Raquel Frizera Vassallo; Dimitra Simeonidou

doi:10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134

Multilevel Observability in Cloud Orchestration

Raquel Frizera Vassallo, Alexandre Pereira do Carmo, Felippe M. de Queiroz, Anilton S. Garcia, Raquel Frizera Vassallo, Dimitra Simeonidou

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

560 Downloads (Pure)

Abstract

Cloud infrastructures can provide resource sharing between many applications and usually can meet the requirements of most of them. However, in order to enable an efficient usage of these resources, automatic orchestration is required. Commonly, automatic orchestration tools are based on the observability of the infrastructure itself, but that is not enough in some cases. Certain classes of applications have specific requirements that are difficult to meet, such as low latency, high bandwidth and high computational power. To properly meet these requirements, orchestration must be based on multilevel observability, which means collecting data from both the application and the infrastructure levels. Thus in this work we developed a platform aiming to show how multilevel observability can be implemented and how it can be used to improve automatic orchestration in cloud environments. As a case study, an application of computer vision and robotics, with very demanding requirements, was used to perform two experiments and illustrate the issues addressed in this paper. The results confirm that cloud orchestration can largely benefit from multilevel observability by allowing specific application requirements to be met, as well as improving the allocation of infrastructure resources.

Original language	English
Title of host publication	2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018)
Subtitle of host publication	Proceedings of a meeting held 12-15 August 2018, Athens, Greece
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	770-775
Number of pages	6
ISBN (Electronic)	9781538675182
ISBN (Print)	9781538675199
DOIs	https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134
Publication status	Published - Feb 2019

Keywords

Intelligent spaces
Observability
cloud computing

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10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134

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Frizera Vassallo, R., Pereira do Carmo, A., de Queiroz, F. M., Garcia, A. S., Frizera Vassallo, R., & Simeonidou, D. (2019). Multilevel Observability in Cloud Orchestration. In 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018): Proceedings of a meeting held 12-15 August 2018, Athens, Greece (pp. 770-775). [8511977] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134

Frizera Vassallo, Raquel ; Pereira do Carmo, Alexandre ; de Queiroz, Felippe M. ; Garcia, Anilton S. ; Frizera Vassallo, Raquel ; Simeonidou, Dimitra. / Multilevel Observability in Cloud Orchestration. 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018): Proceedings of a meeting held 12-15 August 2018, Athens, Greece. Institute of Electrical and Electronics Engineers (IEEE), 2019. pp. 770-775

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Frizera Vassallo, R, Pereira do Carmo, A, de Queiroz, FM, Garcia, AS, Frizera Vassallo, R & Simeonidou, D 2019, Multilevel Observability in Cloud Orchestration. in 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018): Proceedings of a meeting held 12-15 August 2018, Athens, Greece., 8511977, Institute of Electrical and Electronics Engineers (IEEE), pp. 770-775. https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134

Multilevel Observability in Cloud Orchestration. / Frizera Vassallo, Raquel; Pereira do Carmo, Alexandre; de Queiroz, Felippe M.; Garcia, Anilton S.; Frizera Vassallo, Raquel; Simeonidou, Dimitra.

2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018): Proceedings of a meeting held 12-15 August 2018, Athens, Greece. Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 770-775 8511977.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Frizera Vassallo R, Pereira do Carmo A, de Queiroz FM, Garcia AS, Frizera Vassallo R, Simeonidou D. Multilevel Observability in Cloud Orchestration. In 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, 16th International Conference on Pervasive Intelligence and Computing, 4th International Conference on Big Data Intelligence and Computing and 3rd Cyber Science and Technology Congress (DASC-PICom-DataCom-CyberSciTech 2018): Proceedings of a meeting held 12-15 August 2018, Athens, Greece. Institute of Electrical and Electronics Engineers (IEEE). 2019. p. 770-775. 8511977 https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00134