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Scaling Policy Assignment in Containerized Environment

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DOI:

https://doi.org/10.31224/3882

Keywords:

Data security, Cloud computing , Machine learning, Distributed computing

Abstract

In containerized environments, securing inter-service communication is paramount, and Mutual TLS (mTLS) offers a robust solution. However, traditional mTLS implementations face challenges in scaling and scalable environments.

This paper introduces a novel approach to mTLS using Scaling Policy Assignment (SPA), which leverages Kubernetes’ native capabilities to automate and optimize policy application based on service requirements. SPA enables flexible and efficient mTLS enforcement, scaling seamlessly with the environment’s complexity.

This approach enhances security, reduces manual configuration, and ensures consistent policy application across services.

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Posted

2024-09-09 — Updated on 2024-09-16

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Added new citations and corrections based on review