Authors :
Muka Kabeya Arsene; Oshasha Oshasha Fiston; Musas A Musas Andre; Kabeya Mukosayi Jospeh; Tshielo Koka Souvient; Kobalanga Liamba Pathy Cedrick
Volume/Issue :
Volume 11 - 2026, Issue 5 - May
Google Scholar :
https://tinyurl.com/2esern5u
Scribd :
https://tinyurl.com/yhuw8fub
DOI :
https://doi.org/10.38124/ijisrt/26May695
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The complexity of distributed systems is ever growing, and cloud-native architectures have become the de facto
standard for modern software engineering, further solidifying REST APIs as its centerpiece. Thanks to the availability of
frameworks like Spring Boot, programmers can develop microservices that are scalable and modular at a rapid pace. However,
although flexible, most API frameworks are statically configured and do not support dynamic adaptation at runtime to changes
in workload, user behaviour, or infrastructure environment. In this paper, we present a complete self-adaptive REST API
paradigm by the means of incorporating live observability, smart decision-making, and runtime reconfiguration within Spring
Boot-based microservices. The architecture proposed in this paper brings a feedback-driven approach which keeps track of the
system’s behavior, context-aware data analysis, and incremental adaptions at runtime so as to enhance its performance,
resiliency, and resource consumption. By complementing classical API design techniques with adaptative intelligence, this work
paves the way towards the potential next generation of autonomous software systems that are expected to run successfully in
highly dynamic and unforeseeable environments.
References :
- R. Johnson et al., Spring Framework Reference Documentation, 2022.
- P. Jamshidi, C. Pahl, and N. C. Mendonça, “Self-Adaptive Microservices: A Systematic Literature Review,” IEEE Software, vol. 35, no. 3, pp. 56–63, 2018.
- B. Burns and D. Oppenheimer, Designing Distributed Systems, O’Reilly Media, 2018.
- M. Fowler, “Microservices: A Definition of This New Architectural Term,” 2014.
- N. Dragoni et al., “Microservices: Yesterday, Today, and Tomorrow,” Springer, 2017.
- S. Newman, Building Microservices, O’Reilly Media, 2021.
- G. Hohpe and B. Woolf, Enterprise Integration Patterns, Addison-Wesley, 2003.
The complexity of distributed systems is ever growing, and cloud-native architectures have become the de facto
standard for modern software engineering, further solidifying REST APIs as its centerpiece. Thanks to the availability of
frameworks like Spring Boot, programmers can develop microservices that are scalable and modular at a rapid pace. However,
although flexible, most API frameworks are statically configured and do not support dynamic adaptation at runtime to changes
in workload, user behaviour, or infrastructure environment. In this paper, we present a complete self-adaptive REST API
paradigm by the means of incorporating live observability, smart decision-making, and runtime reconfiguration within Spring
Boot-based microservices. The architecture proposed in this paper brings a feedback-driven approach which keeps track of the
system’s behavior, context-aware data analysis, and incremental adaptions at runtime so as to enhance its performance,
resiliency, and resource consumption. By complementing classical API design techniques with adaptative intelligence, this work
paves the way towards the potential next generation of autonomous software systems that are expected to run successfully in
highly dynamic and unforeseeable environments.
