The scalability of modern Web applications has become a key aspect for any business in order to support thousands of concurrent users while reducing its computational costs. If a Web application does not scale, a few hundred users can take the application down and as a consequence cause business problems in their companies. In addition, being able to scale a Web application is not an easy task, as it involves many technical aspects such as architecture design, performance, monitoring and availability that are completely ignored by current Model Driven Web Engineering approaches. In this paper we present a model-based approach that uses runtime transformations for overcoming scalability problems in the applications derived from them. We present our approach by “scaling up” a WebML application under a stress scenario, proving that it provides a “framework“ for overcoming scalability issues.
CITATION STYLE
Luna, E. R., Rivero, J. M., & Cabot, J. (2014). Improving the Scalability of Web Applications with Runtime Transformations. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8541, 430–439. https://doi.org/10.1007/978-3-319-08245-5_28
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