The Rise of AI-Native Cloud Architectures: What Comes After Microservices

Authors

  • Sanjeev Kumar Pellikoduku

Keywords:

Ai-Native Architecture, Gpu-Aware Orchestration, Vector Databases, Agentic Middleware, Machine Learning Operations

Abstract

Cloud architecture is undergoing a fundamental transformation as artificial intelligence becomes deeplyintegrated into infrastructure design. This article examines the emergence of AI-native cloud architectures that transcend the limitations of traditional microservices by treating intelligence as a foundational designprinciple rather than an auxiliary feature

References

Daniel Crankshaw et al., "Clipper: A Low-Latency Online Prediction Serving System," Usenix, March 2017. URL: https://www.usenix.org/system/files/conference/nsdi17/nsdi17-crankshaw.pdf,

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Published

2026-02-17

How to Cite

Sanjeev Kumar Pellikoduku. (2026). The Rise of AI-Native Cloud Architectures: What Comes After Microservices. Journal of Computational Analysis and Applications (JoCAAA), 35(2), 283–291. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4934

Issue

Vol. 35 No. 2 (2026): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.