NEUROFRONT: HARNESSING AI-DRIVEN PREDICTIVE OPTIMIZATION FOR CLOUD-NATIVE FRONT-END PERFORMANCE IN E-COMMERCE PLATFORMS
Keywords:
Front-End Performance Optimization, AI-Driven Predictive Optimization, Cloud-Native E-Commerce Platforms, Machine Learning In Web Development, Server-Side Rendering (SSR)Abstract
Front-end performance optimization is now a critical aspect of web development as more users expect a faster-performing application. This paper aims to pinpoint the standard approaches and tools for front-end performance improvement and discover the possibilities of applying artificial intelligence (AI) and machine learning (ML) tools in this field. Some key areas of optimization are – reducing HTTP requests, optimizing asset management and delivery, enhancing rendering performance by removing render-blocking resources, and image optimization using proper formats and responsive strategies. Other techniques, such as code splitting, lazy loading, and server-side rendering (SSR), enhance the perceived application load time by only loading what is required in the browser. This increases the guarantee for a certain level of performance across devices and, mainly, networks, as applications are initially built with functionalities that are enhanced using JavaScript where the technology is available. AI and ML have developed revolutionary features like predictive prefetching, adaptive content delivery, and automated performance testing, improving front-end performance by analyzing users' patterns and optimizing resource loading. The concepts of edge computing, WebAssembly, and PWAs open new directions for performance enhancement, making it possible to develop applications and deliver app-like experiences through the web. The future development of 5G networks is also expected to improve the mobile web experience by increasing the data rate and minimizing delay. These techniques are integrated into the architecture where CDNs are to be used to serve the static assets. The proposed architecture integrates all these techniques where static assets are served through CDNs; first, HTML is generated through server-side rendering, JavaScript bundles are dynamically loaded, service workers are used for offline capability, and an API layer has GraphQL and WebSocket connections for real-time updates. This integrated approach guarantees high-performance applications, adequately fitting users' needs and demands. Developers should follow innovative trends and use further technologies to build efficient apps that meet user expectations in a constantly competitive world.
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