RESEARCH OF THE WEB APPLICATION PERFORMANCE ANALYSIS TOOLS TO IDENTIFY AND SOLVE PERFORMANCE ISSUES

Abstract

The article reviews and explores web application performance analysis tools to identify and resolve performance issues, and explores the main tools and methods for analyzing web application performance in order to identify and resolve issues that affect their efficiency and productivity. Web applications are an important component of the modern Internet environment, and performance issues can negatively impact user experience and business results. Web application performance assessment involves the use of specialized tools for monitoring, profiling, and testing, which allows you to quickly identify bottlenecks in the system.

In the modern digital environment, web applications are essential for user interaction, data processing, and providing various online services. However, the increasing complexity of such applications is often accompanied by performance issues that negatively affect page load speed, availability, and user experience. Performance problems can arise from various factors, such as inefficient code, server errors, poorly optimized database queries, or unforeseen network failures. Therefore, effective performance analysis and diagnostics of web applications are critical to ensuring their stable operation and meeting user demands. This study examines tools for performance analysis of web applications that help identify and resolve issues that reduce their efficiency. The main objective of the research is to review modern methods and tools for monitoring, profiling, load testing, and optimizing the performance of web applications. The study covers popular tools such as New Relic, AppDynamics, and Datadog for performance monitoring, Chrome DevTools, Lighthouse, and Xdebug for code profiling, as well as Apache JMeter, Gatling, and LoadRunner for load testing. The paper also explores the process of detecting performance issues, which involves several stages: data collection, metrics analysis, code profiling, and load testing. It explains how these tools can be used to identify "bottlenecks" in an application—problems that slow it down, such as slow page loading, poor database query performance, or low capacity for handling a big number of concurrent requests. 

After identifying the issues, optimization becomes a key part of the process. Various methods are applied for optimization, such as caching, reducing media file sizes, optimizing SQL queries, using asynchronous code, improving API interactions, and others. An important aspect of the research is understanding how integrating these tools into the development process allows for a reduction in application response time and enhances the user experience. The paper also emphasizes future trends in the development of performance analysis tools, including the implementation of artificial intelligence for automatic problem detection and resolution, as well as the integration of new analysis methods, such as real-world testing or simulation-based approaches. It is expected that with the advancement of technology, these tools will become more accessible, automated, and intuitive, enabling faster and more accurate detection of problems and ensuring high performance of web applications in real-time. 

Thus, this study highlights the importance of a comprehensive approach to performance analysis and optimization of web applications and demonstrates how the effective use of modern tools and techniques can significantly improve the efficiency of web application development and maintenance, ensuring stable and fast performance.