research-article

Applying Architectural Templates for Design-Time Scalability and Elasticity Analyses of SaaS Applications

Author:

Sebastian LehrigAuthors Info & Claims

HotTopiCS '14: Proceedings of the 2nd International Workshop on Hot Topics in Cloud service Scalability

Article No.: 2, Pages 1 - 8

https://doi.org/10.1145/2649563.2649573

Published: 22 March 2014 Publication History

HotTopiCS '14: Proceedings of the 2nd International Workshop on Hot Topics in Cloud service Scalability

Applying Architectural Templates for Design-Time Scalability and Elasticity Analyses of SaaS Applications

Pages 1 - 8

Abstract
References

Abstract

Software architects plan, model, and analyze architectures of large software like Software-as-a-Service (SaaS) applications. The scalability and elasticity of these applications is crucially impacted by architects' early decision for an architectural style. However, whether this decision fostered scalability and elasticity can currently only be tested with the final application deployed in the target cloud computing environment. This process leads to the high risk of unsatisfying scalability/elasticity and expensive re-implementations.

To tackle this problem, we propose scalability/elasticity analyses using the architectural template (AT) language, a constraint language to specify templates (based on architectural styles) of component models for early quality analyses. This work-in-progress paper provides a first formalization of the AT language and investigates its applicability to analyze the scalability and elasticity of SaaS applications at early design-time by using a 3-tier example scenario. Our results indicate the language is applicable to such 3-tier scenarios.

References

[1]

Amazon.com Inc. AWS elastic beanstalk. http://aws.amazon.com/elasticbeanstalk/, Last visited: 30 Jan 2014.

[2]

M. Becker, S. Becker, and J. Meyer. SimuLizar: design-time modelling and performance analysis of self-adaptive systems. In Proceedings of Software Engineering 2013 (SE2013), Aachen, 2013.

[3]

M. Becker, M. Luckey, and S. Becker. Model-driven performance engineering of self-adaptive systems: a survey. In QoSA '12, pages 117--122, New York, 2012. ACM.

Digital Library

[4]

S. Becker, H. Koziolek, and R. Reussner. The palladio component model for model-driven performance prediction. Journal of Systems and Software, 82(1), Jan. 2009.

Digital Library

[5]

F. Buschmann, R. Meunier, H. Rohnert, P. Sommerlad, M. Stal, and M. Stal. Pattern-Oriented Software Architecture Volume 1: A System of Patterns. Wiley, volume 1 edition, Aug. 1996.

Digital Library

[6]

R. Carnap. Meaning and Necessity: A Study in Semantics and Modal Logic. Midway reprints. University of Chicago Press, 1988.

[7]

T. Erl, R. Puttini, and Z. Mahmood. Cloud Computing: Concepts, Technology and Design. Prentice Hall PTR, 2013.

Digital Library

[8]

R. Fielding and R. Taylor. Principled design of the modern web architecture, 2000.

[9]

Google Inc. Google app engine. http://developers.google.com/appengine/, Last visited: 30 Jan 2014.

[10]

N. R. Herbst, S. Kounev, and R. Reussner. Elasticity: What it is, and What it is Not. In Proceedings of the 10th International Conference on Autonomic Computing (ICAC 2013), San Jose, CA, June 24--28, 2013.

[11]

T. Kühne. Matters of (meta-)Modeling. Software and System Modeling, 5(4):369--385, 2006.

[12]

H. Koziolek. Performance evaluation of component-based software systems: A survey. Perform. Eval., 67(8):634--658, Aug. 2010.

Digital Library

[13]

H. Koziolek. The SPOSAD architectural style for multi-tenant software applications. In Proc. 9th Working IEEE/IFIP Conf. on Software Architecture, pages 320--327. IEEE, July 2011.

Digital Library

[14]

S. Lehrig. Architectural templates: Engineering scalable SaaS applications based on architectural styles. In Proceedings of the MODELS 2013 Doctoral Symposium co-located with the 16th International ACM/IEEE Conference on Model Driven Engineering Languages and Systems (MODELS 2013), volume 1071, pages 48--55, Miami, USA, 2013. CEUR-WS.org.

[15]

P. Mell and T. Grance. The NIST definition of cloud computing. NIST Special Publication, 145(6):7, 2011.

[16]

A. Mesbah and A. van Deursen. A component- and push-based architectural style for ajax applications. Journal of Systems and Software, 81(12):2194--2209, 2008.

Digital Library

[17]

Microsoft Corporation. Microsoft windows azure. http://www.windowsazure.com/, Last visited: 30 Jan 2014.

[18]

mOSAIC EU Project. mOSAIC: open-source API and platform for multiple clouds. http://www.mosaic-cloud.eu/, Last visited: 30 Jan 2014.

[19]

M. Shaw and P. C. Clements. A field guide to boxology: Preliminary classification of architectural styles for software systems. In Proceedings of the 21st International Computer Software and Applications Conference, pages 6--13. IEEE, 1997.

Digital Library

[20]

R. Taylor, N. Medvidovic, and E. Dashofy. Software Architecture: Foundations, Theory, and Practice. Wiley, 2009.

Digital Library

[21]

W.-T. Tsai, X. Sun, and J. Balasooriya. Service-oriented cloud computing architecture. In ITNG'10, pages 684--689, Washington, DC, USA, 2010. IEEE.

Digital Library

Cited By

Aleem SAhmed FBatool RKhattak A(2021)Empirical Investigation of Key Factors for SaaS ArchitectureIEEE Transactions on Cloud Computing10.1109/TCC.2019.29062999:3(1037-1049)Online publication date: 1-Jul-2021
https://doi.org/10.1109/TCC.2019.2906299
Heinrich RHenss JKoch SReussner R(2021)Challenges in the Evolution of Palladio—Refactoring Design Smells in a Historically-Grown Approach to Software Architecture AnalysisComposing Model-Based Analysis Tools10.1007/978-3-030-81915-6_11(235-257)Online publication date: 18-Jul-2021
https://doi.org/10.1007/978-3-030-81915-6_11
Kroß JKrcmar H(2019)PerTract: Model Extraction and Specification of Big Data Systems for Performance Prediction by the Example of Apache Spark and HadoopBig Data and Cognitive Computing10.3390/bdcc30300473:3(47)Online publication date: 9-Aug-2019
https://doi.org/10.3390/bdcc3030047
Show More Cited By

Index Terms

Applying Architectural Templates for Design-Time Scalability and Elasticity Analyses of SaaS Applications
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

Recommendations

Scalability, Elasticity, and Efficiency in Cloud Computing: a Systematic Literature Review of Definitions and Metrics
QoSA '15: Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures

Context: In cloud computing, there is a multitude of definitions and metrics for scalability, elasticity, and efficiency. However, stakeholders have little guidance for choosing fitting definitions and metrics for these quality properties, thus leading ...
Monitoring-based auto-scalability across hybrid clouds
SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing

Cloud computing is a relatively new type of Internet-based computing that becomes more and more popular. Using methods like virtualization, adopting architectures based on microservices, automation of building and deployment processes, Cloud could ...
A cloud-based TaaS infrastructure with tools for SaaS validation, performance and scalability evaluation
CLOUDCOM '12: Proceedings of the 2012 IEEE 4th International Conference on Cloud Computing Technology and Science (CloudCom)

With the fast advancements in cloud computing and software- as-a-service (SaaS), testing and evaluation of cloud-based software and SaaS applications became an important task for engineers. Since most existing tools are not developed to support cloud-...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

HotTopiCS '14: Proceedings of the 2nd International Workshop on Hot Topics in Cloud service Scalability

March 2014

39 pages

ISBN:9781450330596

DOI:10.1145/2649563

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

SAP
SPEC: SPEC Research Group

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

HotTopiCS '14

HotTopiCS '14: International Workshop on Hot Topics in Cloud service Scalability

March 22, 2014

Dublin, Ireland

Acceptance Rates

Overall Acceptance Rate 10 of 15 submissions, 67%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
119
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Aleem SAhmed FBatool RKhattak A(2021)Empirical Investigation of Key Factors for SaaS ArchitectureIEEE Transactions on Cloud Computing10.1109/TCC.2019.29062999:3(1037-1049)Online publication date: 1-Jul-2021
https://doi.org/10.1109/TCC.2019.2906299
Heinrich RHenss JKoch SReussner R(2021)Challenges in the Evolution of Palladio—Refactoring Design Smells in a Historically-Grown Approach to Software Architecture AnalysisComposing Model-Based Analysis Tools10.1007/978-3-030-81915-6_11(235-257)Online publication date: 18-Jul-2021
https://doi.org/10.1007/978-3-030-81915-6_11
Kroß JKrcmar H(2019)PerTract: Model Extraction and Specification of Big Data Systems for Performance Prediction by the Example of Apache Spark and HadoopBig Data and Cognitive Computing10.3390/bdcc30300473:3(47)Online publication date: 9-Aug-2019
https://doi.org/10.3390/bdcc3030047
Heinrich RKoziolek AReussner RBecker SMedvidovic NMirakhorli MMalek SGarcia JCai YKazman RXiao L(2019)Infrastructure for modeling and analyzing the quality of software architecturesProceedings of the 2nd International Workshop on Establishing a Community-Wide Infrastructure for Architecture-Based Software Engineering10.1109/ECASE.2019.00009(2-5)Online publication date: 27-May-2019
https://dl.acm.org/doi/10.1109/ECASE.2019.00009
Heinrich RWerle DKlare HReussner RKramer MBecker SHappe JKoziolek HKrogmann KChaudron MCrnkovic IChechik MHarman M(2018)The palladio-bench for modeling and simulating software architecturesProceedings of the 40th International Conference on Software Engineering: Companion Proceeedings10.1145/3183440.3183474(37-40)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3183440.3183474
Aleem SBatool RAhmed FKhatak AUllah R(2017)Architecture guidelines for SaaS development processProceedings of the 2017 International Conference on Cloud and Big Data Computing10.1145/3141128.3141136(94-99)Online publication date: 17-Sep-2017
https://dl.acm.org/doi/10.1145/3141128.3141136
Kistowski JHerbst NKounev SGroenda HStier CLehrig S(2017)Modeling and Extracting Load Intensity ProfilesACM Transactions on Autonomous and Adaptive Systems10.1145/301959611:4(1-28)Online publication date: 10-Jan-2017
https://dl.acm.org/doi/10.1145/3019596
KroB JKrcmar H(2017)Model-Based Performance Evaluation of Batch and Stream Applications for Big Data2017 IEEE 25th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)10.1109/MASCOTS.2017.21(80-86)Online publication date: Sep-2017
https://doi.org/10.1109/MASCOTS.2017.21
Lehrig SHilbrich MBecker S(2017)The architectural template method: templating architectural knowledge to efficiently conduct quality‐of‐service analysesSoftware: Practice and Experience10.1002/spe.251748:2(268-299)Online publication date: 25-Aug-2017
https://doi.org/10.1002/spe.2517

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten