A Dockerized Approach to Dynamic Endpoint Management for RESTful Application Programming Interfaces in Internet of Things Ecosystems

The growth of IoT devices has generated an increasing demand for effective, agile, and scalable deployment frameworks. Traditional IoT architectures are generally strained by interoperability, real-time responsiveness, and resource optimization due to inherent complexity in managing heterogeneous devices and large-scale deployments. While containerization and dynamic API frameworks are seen as solutions, current methodologies are founded primarily on static API architectures that cannot be adapted in real time with evolving data structures and communication needs. Dynamic routing has been explored, but current solutions lack database schema flexibility and endpoint management. This work presents a Dockerized framework that integrates Dynamic RESTful APIs with containerization to achieve maximum flexibility and performance in IoT configurations. With the use of FastAPI for asynchronous processing, the framework dynamically scales API schemas as per real-time conditions, achieving maximum device interaction efficiency. Docker provides guaranteed consistent, portable deployment across different environments. An emulated IoT environment was used to measure significant performance parameters, including functionality, throughput, response time, and scalability. The evaluation shows that the framework maintains high throughput, with an error rate of 3.11% under heavy loads and negligible latency across varying traffic conditions, ensuring fast response times without compromising system integrity. The framework demonstrates significant advantages in IoT scenarios requiring the addition of new parameters or I/O components where dynamic endpoint generation enables immediate monitoring without core application changes. Architectural decisions involving RESTful paradigms, microservices, and containerization are also discussed in this paper to ensure enhanced flexibility, modularity, and performance. The findings provide a valuable addition to dynamic IoT API framework design, illustrating how dynamic, Dockerized RESTful APIs can improve the efficiency and flexibility of IoT systems.

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Publication Details

Journal
Sensors
Published
2025-05-09
DOI
https://doi.org/10.3390/s25102993
Citations
1
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
3.25
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article

A Dockerized Approach to Dynamic Endpoint Management for RESTful Application Programming Interfaces in Internet of Things Ecosystems

Nkateko Mabunda, Ahmed Abdi Yusuf Ali, Ebenhezer Mabotha
1 citations
Sensors
Cloud Computing and Resource Management
3.25
article

A Dockerized Approach to Dynamic Endpoint Management for RESTful Application Programming Interfaces in Internet of Things Ecosystems

Nkateko Mabunda, Ahmed Abdi Yusuf Ali, Ebenhezer Mabotha
article en
1 citations

Abstract

The growth of IoT devices has generated an increasing demand for effective, agile, and scalable deployment frameworks. Traditional IoT architectures are generally strained by interoperability, real-time responsiveness, and resource optimization due to inherent complexity in managing heterogeneous devices and large-scale deployments. While containerization and dynamic API frameworks are seen as solutions, current methodologies are founded primarily on static API architectures that cannot be adapted in real time with evolving data structures and communication needs. Dynamic routing has been explored, but current solutions lack database schema flexibility and endpoint management. This work presents a Dockerized framework that integrates Dynamic RESTful APIs with containerization to achieve maximum flexibility and performance in IoT configurations. With the use of FastAPI for asynchronous processing, the framework dynamically scales API schemas as per real-time conditions, achieving maximum device interaction efficiency. Docker provides guaranteed consistent, portable deployment across different environments. An emulated IoT environment was used to measure significant performance parameters, including functionality, throughput, response time, and scalability. The evaluation shows that the framework maintains high throughput, with an error rate of 3.11% under heavy loads and negligible latency across varying traffic conditions, ensuring fast response times without compromising system integrity. The framework demonstrates significant advantages in IoT scenarios requiring the addition of new parameters or I/O components where dynamic endpoint generation enables immediate monitoring without core application changes. Architectural decisions involving RESTful paradigms, microservices, and containerization are also discussed in this paper to ensure enhanced flexibility, modularity, and performance. The findings provide a valuable addition to dynamic IoT API framework design, illustrating how dynamic, Dockerized RESTful APIs can improve the efficiency and flexibility of IoT systems.

SensorsVol. 25(10)
University of Johannesburg (ZA)
Openalex Percentile: Top 9%
Cloud Computing and Resource Management
3.25
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