TY - GEN
T1 - Performance Evaluation of a Dynamic RESTful API Using FastAPI, Docker and Nginx
AU - Mabotha, Ebenhezer
AU - Mabunda, Nkateko E.
AU - Ali, Ahmed
N1 - Publisher Copyright:
©2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper provides a performance evaluation of a dynamic RESTful API architecture suitable for IoT deployments. The framework, developed with Python's FastAPI, PostgreSQL, and Nginx and containerized with Docker, was tested for flexibility, reliability, and efficiency under various scenarios. The evaluation focused on key operational indicators such as response time, throughput, load handling, and security. Functional testing confirmed the functionality of essential API endpoints used for dynamic CRUD operations, providing consistent response accuracy. Load testing using Apache JMeter revealed that the system maintained an average response time of 95ms under moderate loads and could handle many concurrent requests with negligible performance deterioration, demonstrating its ability. The throughput remained consistent even at high traffic volumes, demonstrating its suitability for dynamic IoT applications. Security testing, aided by Nginx's rate-limiting feature, demonstrated the framework's resistance to popular threats such as SQL injection and DDoS. The results show that the dynamic API framework is ideal for expandable IoT installations, providing high availability, low latency, and responsiveness in real-time applications. These results demonstrate its capacity to handle demanding IoT scenarios while maintaining performance dependability and security. This paper provides the testing methods and performance results contributing to the framework's fit for real-world IoT use cases.
AB - This paper provides a performance evaluation of a dynamic RESTful API architecture suitable for IoT deployments. The framework, developed with Python's FastAPI, PostgreSQL, and Nginx and containerized with Docker, was tested for flexibility, reliability, and efficiency under various scenarios. The evaluation focused on key operational indicators such as response time, throughput, load handling, and security. Functional testing confirmed the functionality of essential API endpoints used for dynamic CRUD operations, providing consistent response accuracy. Load testing using Apache JMeter revealed that the system maintained an average response time of 95ms under moderate loads and could handle many concurrent requests with negligible performance deterioration, demonstrating its ability. The throughput remained consistent even at high traffic volumes, demonstrating its suitability for dynamic IoT applications. Security testing, aided by Nginx's rate-limiting feature, demonstrated the framework's resistance to popular threats such as SQL injection and DDoS. The results show that the dynamic API framework is ideal for expandable IoT installations, providing high availability, low latency, and responsiveness in real-time applications. These results demonstrate its capacity to handle demanding IoT scenarios while maintaining performance dependability and security. This paper provides the testing methods and performance results contributing to the framework's fit for real-world IoT use cases.
KW - API
KW - Deployment
KW - Docker
KW - FastAPI
KW - Interface
KW - IoT
KW - JMeter
KW - RESTful
UR - http://www.scopus.com/inward/record.url?scp=86000713773&partnerID=8YFLogxK
U2 - 10.1109/GEC61857.2024.10881712
DO - 10.1109/GEC61857.2024.10881712
M3 - Conference contribution
AN - SCOPUS:86000713773
T3 - IEEE Global Energy Conference 2024, GEC 2024
SP - 174
EP - 181
BT - IEEE Global Energy Conference 2024, GEC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Global Energy Conference, GEC 2024
Y2 - 4 December 2024 through 6 December 2024
ER -