Production-Grade Kubernetes on AWS EKS

Journal of Advanced Engineering Technology and Management 

ISSSN (Online): 3049-3684

Volume: 2 Issue: 1 | Open Access | 22 May 2026

Production-Grade Kubernetes on AWS EKS: Design Patterns for Security, Scalability, and Cost Optimization

Avneet Bansal1

1Independent Researcher, avneetbansal9815@gmail.com

Abstract

Container orchestration technologies have evolved as the underlying enabling platforms for cloud-native computing as enterprise use-cases for distributed applications at scale call for resiliency, automation, portability, and elasticity in operations. Kubernetes has established itself as the leader in this space given its declarative approach to configuration management, extensibility, and ecosystem maturity (Saleh and Karslioglu, 2021). Running Kubernetes at scale in production environments poses a range of complex architectural decisions around aspects such as security and governance, scalability and elasticity of workloads, observability and monitoring, and cost optimization of underlying infrastructure. Services such as Amazon Elastic Kubernetes Service (EKS) have simplified operational overhead associated with running Kubernetes clusters by offering managed control-plane components while still allowing full flexibility of Kubernetes thereby helping teams move faster with their cloud-native transformation journeys. Production-ready setups with EKS however require teams to make strategic design decisions.

In this paper, we explore architectural considerations and decision-making strategies around operating production-ready Kubernetes clusters on Amazon EKS across three key aspects - Security, Scalability, and Cost-Optimization. We review recent academic work at the intersection of cloud-native computing, microservices, infrastructure for machine learning and AI workloads, zero-trust security, and Site Reliability Engineering (SRE) for Kubernetes to derive some of the current industry practices and highlight architectural patterns that can be applied to production clusters. In particular, we discuss topics such as identity federation, secrets management, policy enforcement, runtime security, and zero-trust security under Security; cluster autoscaling, pod scheduling strategies, multi-AZ fault-tolerance, service mesh, and workload isolation under Scalability; and cluster right-sizing, spot instances, storage optimization, cost-governance for monitoring and logging, and cost-aware scheduling under Cost-Optimization.

Our review illustrates that success with EKS at production-grade workloads is less about adopting Kubernetes and more about making the right set of tradeoffs and design decisions around security-by-default, scalability, and cost-governance as part of the application infrastructure. Recent developments around cluster operational practices being informed by AI/ML (Sannareddy, 2024), auto-remediation capabilities (Kumar, 2026), and Kubernetes for managing cloud-native AI workloads (Patrick et al., 2023) further highlight the value of investing in sound Kubernetes engineering practices.

Keywords: Kubernetes, Amazon EKS, cloud-native architecture, container orchestration, zero trust security, autoscaling, cost optimization, DevOps, microservices, observability.

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