Optimizing REST API Reliability in Cloud-Based Insurance Platforms for Education and Healthcare Clients
Lalith Sriram Datla · International Journal of Artificial Intelligence Data Science and Machine Learning · 2023
In today’s dynamic digital environment, the education and healthcare industries are in urgent need of the elixir of the insurance platforms. These sectors, today, more than in many other industries, require 24/7 unceasing access to critical services, strict data safety, and fault-tolerant designs, as well as seamless user experiences. This discussion aims at giving more insight into how cloud-based infrastructures can be reshaped and made more efficient for the consistent performance of REST APIs, since these are among the first things that connect the user-facing applications and the backend insurance systems. Only sectors like education and healthcare experience greater variability in user load compared to conventional sectors; for example, they are bustling during the academic year but quite empty during holidays, with new enrollments and adherence to codes of conduct affecting API quality consistency. The write-up considers the comparison of some of the custom strategies used for the autoscaling issue, like the one that may handle the request volumes up and down without the user feeling the effect of latency, another that shows the resilient system in case of partial failures, and also still another type of autoscaling used to count the number of nodes. This technique slightly overlaps with the uninterrupted mode of services in that both are used to avoid a gap in services, but sentries neither detect nor resolve issues. By outlining these points, the authors prove that these strategies can fit into the CI/CD pipelines, which remain highly viable even in case of instability. RTLC (Reliability, Testability, Loadability, and Compatibility) also refers to the idea of planning to add the reliability feature in the process of software development