Technologies and Methods for Optimizing Web Application Performance
Keywords:
web performance optimization, server-side rendering, lazy loading, code splitting, caching strategies, content delivery networks, database optimization, GraphQL, edge computing, front-end techniquesAbstract
The article reviews modern technologies and methods applied to optimize web application performance, emphasizing the direct impact of site speed on user experience, business performance, and competitive positioning. The authors analyze contemporary approaches for enhancing both front-end and back-end performance. Front-end strategies discussed include code splitting, lazy loading, server-side rendering (SSR), image optimization, and minimizing render-blocking resources. Back-end methods encompass various caching strategies, database query optimization, effective API design—particularly comparing GraphQL and REST—and deployment of Content Delivery Networks (CDNs) alongside edge computing solutions. A structured review methodology was applied, synthesizing recent peer-reviewed literature, expert reports, and empirical case studies from industry settings published within the past five years. Quantitative data are provided, illustrating significant performance improvements, including latency reduction, increased throughput, and enhanced user interaction metrics. The authors highlight practical implementation considerations and trade-offs inherent to each technique. Presented findings contribute valuable insights for developers, system architects, and researchers aiming to deliver faster, more reliable, and user-friendly web applications.
References
. Ala-Laurinaho R., Mattila J., Autiosalo J., Hietala J., Laaki H., Tammi K. Comparison of REST and GraphQL Interfaces for OPC UA // Computers. – 2022. – Vol. 11, No. 5. – Article 65. – DOI: https://doi.org/10.3390/computers11050065.
. Tzinos, Iraklis & Limniotis, Konstantinos & Kolokotronis, Nicholas. (2022). Evaluating the performance of post-quantum secure algorithms in the TLS protocol. Journal of Surveillance, Security and Safety. 3. 101-127. 10.20517/jsss.2022.15.
. Ekpobimi H. O., Kandekere R. C., Fasanmade A. A. Conceptual Framework for Enhancing Front-end Web Performance: Strategies and Best Practices // Global Journal of Advanced Research and Reviews. – 2024. – Vol. 2, No. 1. – P. 99–107.
. Jain V. Optimizing Web Performance with Lazy Loading and Code Splitting // International Journal of Core Engineering & Management. – 2022. – URL: https://www.academia.edu/128332078/optimizing_web_performance_with_lazy_loading_and_code_splitting (access date: 04/03/2025).
. John J. Optimizing Application Performance: A Study on the Impact of Caching Strategies on Latency Reduction // International Journal of Computing. – 2024. – May.
. Riet J., Malavolta I., Ghaleb T. Optimise along the way: An industrial case study on web performance // Journal of Systems and Software. – 2023. – Vol. 198. – Article No. 111593. – DOI: 10.1016/j.jss.2022.111593.
. Smith C. Page Speed and Decreased Conversion Rates: 2023 Statistics [Electronic resource] // OuterBox Blog. – Updated August 22, 2024. – URL: https://www.outerboxdesign.com/digital-marketing/page-speed-conversion-statistics/ (accessed: 03.04.2025).
. Super S. How Does Implementing Server-Side Rendering Improve Core Web Vitals? [Electronic resource] // Linkbot Library Q&A. – May 10, 2024. – URL: https://library.linkbot.com/how-does-implementing-server-side-rendering-ssr-improve-core-web-vitals-and-what-are-the-best-practices-for-ssr-setup/ (accessed: 03.04.2025).
. TierPoint. The Strategic Guide to Edge Computing [Electronic resource]. – TierPoint LLC, 2022. – URL: https://www.tierpoint.com/it-strategic-guides/edge-computing/ (accessed: 03.04.2025).
. Ullah, Ihsan & Khan, Muhammad & St-Hilaire, Marc & Faisal, Mohammad & Kim, Hong & Kim, Su. (2021). Task Priority-Based Cached-Data Prefetching and Eviction Mechanisms for Performance Optimization of Edge Computing Clusters. Security and Communication Networks. 2021. 1-10. 10.1155/2021/5541974.
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