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Evaluating Multi-Cloud Portability and Elastic Scaling Across Serverless-Container Platforms

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  • Dac Tuan Thanh Nguyen

    (Department of Computer Science and Information Technology, School of Computing, La Trobe University, Melbourne, Australia)

  • Tony de Souza-Daw

    (Department of Computer Science and Information Technology, School of Computing, La Trobe University, Melbourne, Australia)

Abstract

Multi-cloud adoption is increasingly driven by resilience, regulatory compliance, and vendor independence. Serverless-container platforms such as AWS Fargate, Google Cloud Run, and Azure Container Instances promise portability through similar abstraction models, yet they exhibit differences in configuration semantics and runtime behavior. This study presents a metric-driven evaluation of multi-cloud compatibility using the Cloud Compatibility System, distinguishing between feature-level configuration coverage and empirical execution reliability. Unified container configurations are deployed across providers under controlled conditions to measure execution success, startup latency, and runtime variability. Results show high execution reliability despite limited feature compatibility, revealing a weak correlation between documented configuration support and runtime behavior. These findings highlight the limitations of feature-centric portability assessments and establish an empirically grounded framework for evaluating interoperability in serverless-container environments.

Suggested Citation

  • Dac Tuan Thanh Nguyen & Tony de Souza-Daw, 2026. "Evaluating Multi-Cloud Portability and Elastic Scaling Across Serverless-Container Platforms," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 16(1), pages 1-22, January.
    • Handle: RePEc:igg:jcac00:v:16:y:2026:i:1:p:1-22
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