Secure Cloud-Native Data Integration on AWS Using Microservices, IoT, and Transparent Data Encryption

Cloud-native architectures deployed on Amazon Web Services (AWS) increasingly rely on microservices and Internet of Things (IoT) platforms to support scalable, real-time, and data-intensive applications. While these paradigms improve agility and elasticity, they introduce significant challenges in secure data integration, governance, and regulatory compliance due to highly distributed data flows and expanded attack surfaces. This paper presents a secure cloud-native data integration architecture on AWS that unifies microservices-based application workloads, IoT data ingestion pipelines, and database-level protection using Oracle 19c Transparent Data Encryption (TDE). The proposed architecture maps established design patterns such as service meshes, edge and fog computing, and streaming-based ETL to AWS-native services, enabling encrypted data exchange in transit and robust protection of data at rest without application modifications. A prototype implementation using Amazon EKS, AWS IoT Core, AWS Glue, and Oracle 19c demonstrates scalable ingestion, low-latency processing, and minimal performance overhead from encryption. Experimental results validate that the architecture achieves improved scalability and tail-latency characteristics while maintaining strong data-at-rest security and compliance readiness. The paper further identifies research gaps in AI-driven automation, unified observability, and adaptive security frameworks for future cloud-native and multi-cloud data integration environments.