OPTIMIZING ADOBE EXPERIENCE MANAGER PERFORMANCE: A MULTIFACETED APPROACH TO ENHANCING USER EXPERIENCE AND SYSTEM EFFICIENCY

This article presents a comprehensive framework for ensuring and optimizing application performance in Adobe Experience Manager (AEM), a widely-used content management system. As digital experiences become increasingly crucial for business success, the performance of AEM applications directly impacts user engagement, business continuity, and operational costs. This article examines key performance metrics, including response time, resource utilization, and user experience indicators, and explores advanced monitoring and assessment techniques. We propose a multifaceted optimization strategy encompassing front-end enhancements, back-end improvements, API call optimization, and effective heap memory management. Through case studies of e-commerce and content-heavy portal optimizations, we demonstrate the practical application and efficacy of these strategies. The article also addresses emerging challenges in AEM performance optimization and discusses the potential role of AI and machine learning in future performance management. By offering a systematic approach to continuous monitoring, measurement, and optimization, this study provides valuable insights for developers, system administrators, and business stakeholders seeking to maximize the performance and scalability of their AEM applications.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-04
DOI
https://doi.org/10.5281/zenodo.14034731
Primary Topic
melanin and skin pigmentation
Type
article
Field-Weighted Citation Impact
0.00
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article

OPTIMIZING ADOBE EXPERIENCE MANAGER PERFORMANCE: A MULTIFACETED APPROACH TO ENHANCING USER EXPERIENCE AND SYSTEM EFFICIENCY

Zenodo (CERN European Organization for Nuclear Research)
melanin and skin pigmentation
article

OPTIMIZING ADOBE EXPERIENCE MANAGER PERFORMANCE: A MULTIFACETED APPROACH TO ENHANCING USER EXPERIENCE AND SYSTEM EFFICIENCY

article en

Abstract

This article presents a comprehensive framework for ensuring and optimizing application performance in Adobe Experience Manager (AEM), a widely-used content management system. As digital experiences become increasingly crucial for business success, the performance of AEM applications directly impacts user engagement, business continuity, and operational costs. This article examines key performance metrics, including response time, resource utilization, and user experience indicators, and explores advanced monitoring and assessment techniques. We propose a multifaceted optimization strategy encompassing front-end enhancements, back-end improvements, API call optimization, and effective heap memory management. Through case studies of e-commerce and content-heavy portal optimizations, we demonstrate the practical application and efficacy of these strategies. The article also addresses emerging challenges in AEM performance optimization and discusses the potential role of AI and machine learning in future performance management. By offering a systematic approach to continuous monitoring, measurement, and optimization, this study provides valuable insights for developers, system administrators, and business stakeholders seeking to maximize the performance and scalability of their AEM applications.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 59%
melanin and skin pigmentation
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OPTIMIZING ADOBE EXPERIENCE MANAGER PERFORMANCE: A MULTIFACETED APPROACH TO ENHANCING USER EXPERIENCE AND SYSTEM EFFICIENCY · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS