RESTFUL API PERFORMANCE MODELING: REQUEST PROCESSING ALGORITHMS AND DATA ANALYSIS

Abstract

The text summarizes the positive and negative aspects of creating RESTful APIs in back-end development. It analyzes the current state of REST architecture usage in web technologies and examines modern approaches and tools for developing RESTful APIs, justifying their applicability. Popular frameworks and development environments, such as Express.js, Django REST Framework, and Spring Boot, which are widely used in both startups and large companies, are described. The study highlights key features such as request structuring, HTTP methods, routing standards, and server-side data handling. It emphasizes RESTful APIs for their ease of integration, scalability, and flexibility in client-server application development. The key principles of RESTful API design are outlined, including the use of the GET, POST, PUT, and DELETE methods, proper server response formatting, and standardization of resource paths. Some limitations of the REST approach are noted, such as challenges in handling a large number of resources and issues related to API versioning. The use of these tools and approaches improves the quality of server-side logic, ensures standardized data exchange, and reduces complexity in client-side integration. The application of RESTful APIs in modern web design through frameworks like Express.js, Django REST Framework, and Spring Boot is characterized. A practical example is provided of a small Node.js server using Express to manage a task list with basic CRUD operations. The focus is on optimizing REST requests through various strategies, including caching, pagination, filtering, batch requests, data compression, and asynchronous processing. A methodology for evaluating API performance on a Node.js/Express test server, using Prometheus and Grafana for monitoring, is described. Load testing with a stable request stream allowed for the assessment of the impact of individual optimization methods on throughput, latency, and data volume. Results indicate that asynchronous requests and batch operations yield the highest performance increases, while caching, pagination, filtering, and compression offer moderate improvements. It is emphasized that utilizing combined optimization methods significantly enhances speed, reduces response time and server load, and ensures stable operation of web services, even under conditions of high traffic intensity.