Abstract
In the previous chapter, we have introduced the concepts of cloud computing and serverless computing, their potential advantages, and how they could be used to solve the daily problems in the process of research. But what exactly are these applications in the real world? This chapter introduces the real-world implementation of cloud and serverless computing, discussing potential vendors and free options and how serverless computing is a more recent idea in cloud computing environments that is likely to grow in future years. We also discuss the environmental issues associated with cloud computing infrastructures. Finally, a handful of examples of the application of these technologies in different research fields are considered to illustrate present and potential future applications.
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Notes
- 1.
This is independent of whether the data center is owned by a vendor or a private or public body.
- 2.
At the moment of writing this book, AWS has reported that it will challenge the decision of the DOD of granting the contract to Azure.
References
Hayes B (2008) Cloud computing. Commun ACM 51(7):9–11. https://doi.org/10.1145/1364782.1364786
Distefano S, Puliafito A (2012) Cloud@Home: toward a volunteer cloud. IT Prof 14:27–31. https://doi.org/10.1109/MITP.2011.111
Zimmermann O (2017) Microservices tenets. Comput Sci Res Dev 32(3):301–310. https://doi.org/10.1007/s00450-016-0337-0
Graphite (2019) Graphite. https://graphiteapp.org. Accessed 6 Nov 2019
Grafana (2019) Grafana. https://grafana.com/. Accessed 6 Nov 2019
Firesmith D (2017) Virtualization via containers. https://insights.sei.cmu.edu/sei_blog/2017/09/virtualization-via-containers.html. Accessed 6 Nov 2019
Docker (2019) Docker. https://www.docker.com/. Accessed 6 Nov 2019
Añel JA (2011) The importance of reviewing the code. Commun ACM 54(5):40–41. https://doi.org/10.1145/1941487.1941502
Añel JA (2017) Comment on “Most computational hydrology is not reproducible, so is it really science?” by Christopher Hutton et al. Water Resour Res 53(3):2572–2574. https://doi.org/10.1002/2016WR020190
Stodden V, Seiler J, Ma Z (2018) An empirical analysis of journal policy effectiveness for computational reproducibility. Proc Natl Acad Sci 115(11):2584–2589. https://doi.org/10.1073/pnas.1708290115
Boettiger C (2015) An introduction to Docker for reproducible research. SIGOPS Oper Syst Rev 49(1):71–79. https://doi.org/10.1145/2723872.2723882
Kurtzen GM, Sochat V, Bauer MW (2017) Singularity: scientific containers for mobility of compute. PLoS One 12(5):e0177459. https://doi.org/10.1371/journal.pone.0177459
Kim YM, Poline JB, Dumas G (2018) Experimenting with reproducibility: a case study of robustness in bioinformatics. GigaScience 7(7). https://doi.org/10.1093/gigascience/giy077
Baliga J, Ayre RWA, Hinton K, Tucker RS (2011) Green cloud computing: balancing energy in processing, storage, and transport. Proc IEEE 99(1):149–167. https://doi.org/10.1109/JPROC.2010.2060451
Microsoft (2018) The carbon benefits of cloud computing: a study on the Microsoft Cloud, 25 p. https://www.microsoft.com/en-us/download/details.aspx?id=56950
Wu Y, Lin S, Peng F, Li Q (2019) Methods and application of archeological cloud platform for grand sites based on spatio-temporal big data. ISPRS Int J Geo-Inf 8(9):377. https://doi.org/10.3390/ijgi8090377
Goodess CM, Troccoli A, Acton C, Añel JA, Bett PE, Brayshaw DJ, De Felice M, Dorling SE, Dubus L, Penny L, Percy B, Ranchin T, Thomas C, Trolliet M, Wald L (2019) Advancing climate services for the European renewable energy sector through capacity building and user engagement. Clim Serv 16:100139
Vance TF, Merati N, Yang C, Yuan M (2016) Cloud computing in ocean and atmospheric sciences. Academic, San Diego. https://doi.org/10.1016/C2014-0-04015-4
Zhuang J, Jacob DJ, Gaya JF, Yantosca RM, Lundgren EW, Sulprizio MP, Eastham SD (2019) Enabling immediate access to earth science models through cloud computing: application to the GEOS-Chem Model. Bull Am Meteorol Soc 100:1943–1960. https://doi.org/10.1175/BAMS-D-18-0243.1
Añel JA et al (submitted) Evaluation and intercomparison of cloud computing solutions for climate modelling
Montes D, Añel JA, Pena TF, Uhe P, Wallom, DCH (2017) Enabling BOINC in infrastructure as a service cloud systems. Geosci Model Dev 10:811–826. https://doi.org/10.5194/gmd-10-811-2017
CoCalc (2019) CoCalc. https://cocalc.com/. Accessed 6 Nov 2019
Malawski M, Gajek A, Zima A, Balis B, Figiela K (2019) Serverless execution of scientific workflows: experiments with HyperFlow, AWS Lambda and Google Cloud Functions. Future Gener Comput Syst. https://doi.org/10.1016/j.future.2017.10.029
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Añel, J.A., Montes, D.P., Iglesias, J.R. (2020). From the Beginning to the Future. In: Cloud and Serverless Computing for Scientists. Springer, Cham. https://doi.org/10.1007/978-3-030-41784-0_3
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