Algoritme Jurnal Mahasiswa Teknik Informatika
Vol 6 No 1 (2025): Oktober 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika

Implementasi Proxmox Untuk High Availability Dan Load Balancing Pada Sistem Siak Undiksha

Saskara, Gede Arna Jude (Unknown)
Listartha, I Made Edy (Unknown)
Resika Arthana, I Ketut (Unknown)



Article Info

Publish Date
09 Oct 2025

Abstract

In the digital era, Information and Communication Technology infrastructure has become crucial for organizations. Virtualization serves as a primary solution to enhance server efficiency; however, increasing workloads can impact system performance. Cluster computing is essential to maintain service availability and improve processing speed. Proxmox Cluster with Ceph as a distributed storage solution offers a viable implementation.This study analyzes the performance of Proxmox Ceph Cluster in handling traffic increases to ensure optimal service delivery. The research employs the Network Development Life Cycle (NDLC) methodology, consisting of analysis, design, prototype simulation, implementation, monitoring, and management. Testing was conducted at UPA TIK Undiksha, which previously utilized a monolithic server. The evaluation was based on service availability, resource utilization, throughput, and latency, using Apache JMeter.The results indicate that implementing Proxmox Ceph Cluster improves service availability and optimizes workload distribution compared to monolithic systems. The high availability implementation with Ceph can also handle node failures without disrupting core services. Therefore, adopting Proxmox Ceph Cluster presents a reliable solution for supporting a more efficient and resilient IT infrastructure

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Journal Info

Abbrev

algoritme

Publisher

Subject

Computer Science & IT

Description

Jurnal Algoritme menjadi sarana publikasi artikel hasil temuan Penelitian orisinal atau artikel analisis. Bahasa yang digunakan jurnal adalah bahasa Inggris atau bahasa Indonesia. Ruang lingkup tulisan harus relevan dengan disiplin ilmu seperti: - Machine Learning - Computer Vision, - Artificial ...