Scalable CI/CD Architecture Using Multi-Fleet Controllers and HAProxy for Cluster Management in Kubernetes

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Authors: Srinivas Thotakura
Cited by: 0

Abstract

Modernizing large-scale enterprise systems presents significant challenges due to tightly coupled legacy architectures, complex deployment dependencies, and high operational risks. The transition from monolithic applications to cloud-native microservices orchestrated by Kubernetes further amplifies deployment and scalability concerns, particularly in environments managing thousands of clusters. Traditional Kubernetes management platforms face inherent scalability limitations, creating bottlenecks in deployment governance, observability, and reliability. This paper presents a scalable continuous integration and continuous deployment (CI/CD) architecture leveraging multiple standalone Fleet controllers integrated with HAProxy for centralized routing and cluster management. By adopting a GitOps-driven deployment model using Fleet, combined with deterministic cluster-to-controller assignment and label-based rollout strategies, the proposed architecture efficiently manages over 10,000 Kubernetes clusters. HAProxy enables seamless access to distributed Fleet controllers through path-based routing, significantly reducing operational complexity and infrastructure overhead.The architecture incorporates automated fleet agent registration using SUSE Manager (MLM), eliminating manual intervention and ensuring balanced controller utilization. Performance optimizations—including etcd quota tuning and HAProxy connection scaling—address real-world operational constraints encountered during large-scale deployments. Experimental results demonstrate improved scalability, reduced deployment latency, and enhanced reliability. This work provides a practical reference architecture for enterprises seeking to implement resilient, large-scale Kubernetes CI/CD systems.

Fields of Study & Subjects

Software System Performance and Reliability Mobile Agent-Based Network Management Cloud Computing and Resource Management

Publication details

Journal / source
American International Journal of Computer Science and Technology
Volume
8
Issue
1
Pages
1–8
Publication date
3 January 2026