Event Driven API Automation for Microservices and Server less Architectures
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V4I1P122Keywords:
Microservices, Serverless Architecture, Event-Driven Architecture, Api Automation, Asynchronous Processing, Cloud Computing, Event Brokers, Distributed Systems, Workflow Automation, Scalability, Resilience, Integration PatternsAbstract
The shift of monolithic systems to microservices has changed essentially the way applications are designed that are based on the modern concept. In addition, serverless computing's popularity has extended this change significantly by giving less operational intricacy, on-demand scalability, and execution initiated by events. Services have increased systems that are distributed in a way that makes communication between them the main problem that needs to be solved i.e. communication being scalable, decoupled, and event-driven. Synchronous dependencies, latency, and difficulties in orchestration are brought by conventional API-centric, request-response architectures, especially when interaction occurs among hundreds of diverse microservices functioning at varying workloads and reliability levels. To get beyond these constraints, this research considers the implementation of automated event-driven API workflows which lead to the enhancement of event ingestion, routing, transformation, and orchestration activities through the use of an event bus–centric automation layer together with the managed cloud services. The proposed approach employs rule-based triggers, schema validation, live monitoring, and automated compensation activities to create a communication model that is not only more resilient but also more autonomous. The example provides an explanation of how the coupling of microservices and serverless components can be minimized, the system's elasticity can be increased, and fault isolation can be improved by means of automated event flows via an e-commerce order-processing system. The performance is compared with that of traditional REST-based architectures, and the experimental results show, among other significant improvements, a 47% increase in throughput and a 35% reduction in total processing time. The results provide evidence in support of the automation approach as a means to address the management of complicated event interactions and the establishment of reliable workflows in distributed systems. Next, the paper mentions AI-assisted event routing, predictive workload scaling, and standardized event governance models as the future research and development directions aimed at further automation in event-driven microservices and serverless ecosystems.
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