A REVIEW OF THE IMPACT OF COVID-19 ON SERVERLESS COMPUTING TECHNOLOGY

  • Ese Sophia Mughele University of Delta Agbor, Delta State.
  • Sunday Ovie Okuyade
  • Ifeanyi Mirian Oyem
Keywords: Serverless computing, Cloud Computing, COVID-19

Abstract

The Covid-19 pandemic had a profound effect on technology in general, and serverless computing is no exception. Covid-19 pandemic has shaped the field of serverless computing, and how technology has evolved in response. Serverless computing technology have been adapted to meet the need for remote working, and how the technology has changed in terms of scalability and cost-effectiveness. This pandemic has affected virtually every aspect of daily life as significant measures are being taken to limit the spread of the virus. The pandemic has changed not only the way companies operate, but also the way they have been able to survive. Studies indicate increased requests for cloud services ranging from resident users, particularly for telecommuting, entertainment, commerce, to education, and as a result, causing traffic shifts at the core of the Internet. Covid-19 had such a significant impact on cloud services that there is an unprecedented amount of demand for cloud service providers like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. This study used data from a variety of sources to analyse the impact of serverless computing during the pandemic and to justify its significance for a pandemic-affected business. It also reviewed the pre-Covid, Covid and post-Covid-19 era. Two survey reports were used in this study and the effect of Covid-19 on Serverless computing. This paper emphasizes the benefits and adoption of Serverless computing during the pandemic, in contrast to other studies that concentrated on the impact of the Covid-19 epidemic on the cloud computing environment.

References

Aditya P, Akkus I.E, Beck A, Chen R, Hilt V, Rimac I, Satzke K. and Stein M. (2019) Will serverless computing revolutionize nfv? Proc IEEE 107(4):667–678. https://doi.org/10.1109/JPROC.2019.2898101 DOI: https://doi.org/10.1109/JPROC.2019.2898101

Aggarwal, G. 2021. How the Pandemic has Accelerated Cloud Adoption. Forbes Councils Member. https://www.forbes.com/sites/forbestechcouncil/2021/01/15/how-the-pandemic-has-accelerated-cloud-adoption/?sh=2db0247c6621. (Accessed 19 January, 2024)

Alashhab, Z. R., Anbar, M., Singh, M. M., Leau, Y.-B., Al-Sai, Z. A., & Abu Alhayja’a, S. (2020a). Impact of coronavirus pandemic crisis on technologies and cloud computing applications. Journal of Electronic Science and Technology, 100059. https://doi.org/10.1016/j.jnlest.2020.100059

Alashhab, Z. R., Anbar, M., Singh, M. M., Leau, Y.-B., Al-Sai, Z. A., & Abu Alhayja’a, S. (2020b). Impact of coronavirus pandemic crisis on technologies and cloud computing applications. Journal of Electronic Science and Technology, 100059. https://doi.org/10.1016/j.jnlest.2020.100059 DOI: https://doi.org/10.1016/j.jnlest.2020.100059

Asghar T, Rasool S, Iqbal M.U, Qayyum Z, Mian A.N, Ubakanma G (2018) Feasibility of serverless cloud services for disaster management information systems. In: 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). pp 1054–1057. https://doi. org/10.1109/HPCC/SmartCity/DSS.2018.00175 DOI: https://doi.org/10.1109/HPCC/SmartCity/DSS.2018.00175

Cappellari, M., Belstner, J., Rodriguez, B., & Sedayao, J. (2021). A Cloud-Based Data Collaborative to Combat the COVID-19 Pandemic and to Solve Major Technology Challenges. DOI: https://doi.org/10.3390/fi13030061

Carver B, Zhang J, Wang A. and Cheng Y. (2019) In search of a fast and efficient serverless dag engine. In: 2019 IEEE/ACM Fourth International Parallel Data Systems Workshop (PDSW). pp 1–10. https://doi.org/10. 1109/PDSW49588.2019.00005 DOI: https://doi.org/10.1109/PDSW49588.2019.00005

CBInsight.com, Why Serverless Computing is the Fastest-Growing Cloud Services Segment.https://www.cbinsights.com/research/serverless-cloud-computing/ (Accessed May 16th 2024)

Crespo-Cepeda R, Agapito G, Vazquez-Poletti J.L, and Cannataro M. (2019) Challenges and opportunities of amazon serverless lambda services in bioinformatics. In: Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB ‘19). Association for Computing Machinery, New York DOI: https://doi.org/10.1145/3307339.3343462

Feldmann, A., Wagner, D., Wichtlhuber, M., & Tapiador, J. (2020). The Lockdown Effect : Implications of the COVID-19 Pandemic on Internet The Lockdown Effect : Implications of the COVID-19 Pandemic on Internet Traffic. August. DOI: https://doi.org/10.1145/3419394.3423658

Flexera.com, Flexera Releases 2020 State of the Cloud Report. https://www.flexera.com/about-us/press-center/flexera-releases-2020-state-of-the-cloud-report (Accessed February 20th 2022)

Gokarna M (2021) Reasons behind growing adoption of Cloud after Covid-19 Pandemic and Challenges ahead. arXiv; 2021. Europe PMC Preprint

Haider, A. 2021. COVID-19 driving surge in enterprise cloud adoption – 451 survey. https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/covid-19-driving-surge-in-enterprise-cloud-adoption-8211-451-survey-63869853 (Accessed 19 January)

Horovitz S, Amos R, Baruch O, Cohen T, Oyar T. and Deri A (2019) Faastest - machine learning based cost and performance FAAS optimization. In: Coppola M, Carlini E, D’Agostino D, Altmann J, Bañares JÁ (eds). Economics of Grids, Clouds, Systems, and Services. Springer, Cham. pp 171–186. https://doi.org/10.1007/978-3-030-13342-9_15 DOI: https://doi.org/10.1007/978-3-030-13342-9_15

HoseinyFarahabady M, Lee Y.C, Zomaya AY, Tari Z (2017) A qos-aware resource allocation controller for function as a service (faas) platform. In: Maximilien M, Vallecillo A, Wang J, Oriol M (eds). Service-Oriented Computing. Springer, Cham. pp 241–255. https://doi.org/10.1007/978- 3-319-69035-3_17 DOI: https://doi.org/10.1007/978-3-319-69035-3_17

Jangda, A., Pinckney, D., Brun, Y., & Guha, A. (2019). Formal Foundations of Serverless Computing. In arXiv. arXiv. https://doi.org/10.1145/3360575 DOI: https://doi.org/10.1145/3360575

Jones, E. 2021. Cloud Market Share – a Look at the Cloud Ecosystem in 2020. https://www.linkedin.com/pulse/cloud-market-share-look-ecosystem-2020-edward-jones/ (Accessed 19, 2024).

Jyothylakshmi, K. B. 2023. How has the Global Pandemic Accelerated Cloud Adoption Across Every Industry? https://www.ecloudcontrol.com/how-has-the-global-pandemic-accelerated-cloud-adoption-across-every-industry/ (Accessed 19 January 2024)

Kim Y.K, HoseinyFarahabady M.R, Lee Y.C, Zomaya A.Y, Jurdak R (2018) Dynamic control of cpu usage in a lambda platform. In: 2018 IEEE International Conference on Cluster Computing (CLUSTER). pp 234–244. https://doi.org/10.1109/CLUSTER.2018.00041 DOI: https://doi.org/10.1109/CLUSTER.2018.00041

Kuhlenkamp J, Werner S, Borges M.C, El Tal K. and Tai S. (2019) An evaluation of faas platforms as a foundation for serverless big data processing. In: Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC’19). Association for Computing Machinery, New York. pp 1–9. https://doi.org/10.1145/3344341.3368796 DOI: https://doi.org/10.1145/3344341.3368796

Kratzke, N. (2020). Volunteer down: How COVID-19 created the largest idling supercomputer on earth. Future Internet, 12(6), 98. https://doi.org/10.3390/fi12060098 DOI: https://doi.org/10.3390/fi12060098

Leitner P, Wittern E, Spillner J. and Hummer W (2019) A mixed-method empirical study of function-as-a-service software development in industrial practice. J Syst Softw 149:340–359. https://doi.org/10.1016/j. jss.2018.12.013 DOI: https://doi.org/10.1016/j.jss.2018.12.013

Lynn, T., Rosati, P., Lejeune, A., & Emeakaroha, V. (2017). A Preliminary Review of Enterprise Serverless Cloud Computing (Function-as-a-Service) Platforms. Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, 2017-Decem, 162–169. https://doi.org/10.1109/CloudCom.2017.15 DOI: https://doi.org/10.1109/CloudCom.2017.15

Martins H, Araujo F. and da Cunha P.R (2020) Benchmarking serverless computing platforms. J Grid Comput 18(4):691–709. https://doi.org/10. 1007/s10723-020-09523-1 DOI: https://doi.org/10.1007/s10723-020-09523-1

Misbah, S., Ahmad, A., Butt, M. H., Khan, Y. H., Alotaibi, N. H., & Mallhi, T. H. (2020). A systematic analysis of studies on Corona Virus Disease 19 (COVID-19) from viral emergence to treatment. Journal of the College of Physicians and Surgeons Pakistan, 30(1), S9–S18. https://doi.org/10.29271/jcpsp.2020.Supp1.S9 DOI: https://doi.org/10.29271/jcpsp.2020.Supp1.S9

Mohanty S.K, Premsankar G. and di Francesco M (2018) An evaluation of open source serverless computing frameworks. In: 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). pp 115–120. https://doi.org/10.1109/CloudCom2018.2018.00033 DOI: https://doi.org/10.1109/CloudCom2018.2018.00033

Page, M. J., & Moher, D. (2017). Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review. Systematic reviews, 6(1), 1-14. DOI: https://doi.org/10.1186/s13643-017-0663-8

Report, C. (2020). State of the cloud report.

Shafiei, H., Khonsari, A., & Mousavi, P. (2019). Serverless computing: A survey of opportunities, challenges and applications. ArXiv. https://doi.org/10.31224/osf.io/u8xth DOI: https://doi.org/10.31224/osf.io/u8xth

Shah, R. 2023 Cloud Computing on the Rise: MENA Region Sees Accelerated Public Cloud Adoption. https://www.linkedin.com/pulse/cloud-computing-rise-mena-region-sees-accelerated-public-rasmi-shah/. (Accessed 19 January, 2024).

Shahrad M, Balkind J. and Wentzlaff D. (2019) Architectural implications of function-as-a-service computing. In: Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO ‘52). Association for Computing Machinery, New York. pp 1063–1075. https:// doi.org/10.1145/3352460.3358296 DOI: https://doi.org/10.1145/3352460.3358296

Times of India (2020) The Impact of COVID-19 on the Cloud Computing Industry

http://timesofindia.indiatimes.com/articleshow/75574962.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst. May 7, 2020. (Accessed 19, 2024)

Wang H, Niu D. and Li B (2019) Distributed machine learning with a serverless architecture. In: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. pp 1288–1296. https://doi.org/10.1109/ INFOCOM.2019.8737391 DOI: https://doi.org/10.1109/INFOCOM.2019.8737391

Published
2024-06-30
How to Cite
MugheleE. S., OkuyadeS. O., & OyemI. M. (2024). A REVIEW OF THE IMPACT OF COVID-19 ON SERVERLESS COMPUTING TECHNOLOGY. FUDMA JOURNAL OF SCIENCES, 8(3), 111 - 118. https://doi.org/10.33003/fjs-2024-0803-2478