Analisis Komparatif Performa Image VM Badan Informasi Geospasial Pada Platform Manajemen Cloud: Proxmox, Openstack, dan Opennebula

Adnan, Auditya Maulana (2025) Analisis Komparatif Performa Image VM Badan Informasi Geospasial Pada Platform Manajemen Cloud: Proxmox, Openstack, dan Opennebula. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam upaya mendukung pengelolaan data geospasial nasional secara mandiri dan efisien, Badan Informasi Geospasial (BIG) membutuhkan solusi infrastruktur cloud private yang tidak hanya andal, tetapi juga bebas dari ketergantungan terhadap perangkat lunak komersial seperti VMware. Oleh karena itu, penelitian ini dilakukan untuk membandingkan performa tiga platform manajemen cloud open-source: Proxmox, OpenStack, dan OpenNebula, sebagai alternatif potensial bagi BIG. Studi ini mencakup proses migrasi image virtual machine (VM) aplikasi Palapa dari lingkungan VMware ke masing-masing platform uji, dengan parameter evaluasi meliputi performa CPU, memori, disk I/O, jaringan internal-eksternal, dan skalabilitas terhadap beban pengguna. Pengujian dilakukan dalam lingkungan virtualisasi terkontrol berbasis Proxmox sebagai hypervisor utama. Hasil pengujian menunjukkan bahwa OpenNebula unggul dalam aspek CPU (±4500 Events/s) dan throughput memori (rata-rata 27.099,81 MB/s), serta mencatat kecepatan jaringan internal tertinggi sebesar 52,8 Gbps. Di sisi lain, Proxmox menunjukkan dominasi dalam disk I/O dengan capaian hingga 380 MiB/s dan 97.000 operasi per detik, jauh melampaui OpenStack dan OpenNebula yang hanya mencatat 40–45 MiB/s dan ±11.000 ops/s. Pada uji skalabilitas berbasis web load menggunakan Apache JMeter dengan 2000 pengguna, Proxmox mencatat error rate terendah (9,5%) dengan waktu respons rata-rata 7,2 detik, sementara OpenNebula memiliki respons tercepat (6,4 detik) namun error rate lebih tinggi (15,5%), dan OpenStack berada di tengah dengan waktu respons 7,6 detik dan error rate 14%. Berdasarkan keseluruhan hasil, OpenNebula direkomendasikan untuk kebutuhan komputasi dan jaringan berkecepatan tinggi, sedangkan Proxmox lebih sesuai untuk lingkungan skala besar yang menuntut stabilitas sistem dan efisiensi disk, dan OpenStack dapat dipertimbangkan sebagai opsi seimbang antara performa dan kestabilan.
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In an effort to support the independent and efficient management of national geospatial data, the Geospatial Information Agency (BIG) needed a private cloud Infrastructure solution that was not only reliable, but also free from dependence on commercial software such as VMware. Therefore, this study was conducted to compare the performance of three open-source cloud management platforms: Proxmox, OpenStack, and OpenNebula, as potential alternatives to BIG. The study covers the process of migrating Palapa application virtual machine (VM) images from the VMware environment to each test platform, with evaluation parameters including CPU performance, memory, disk I/O, internal-external networking, and scalability to user loads. The test was conducted in a Proxmox-based controlled virtualization environment as the primary hypervisor. The test results showed that OpenNebula excelled in terms of CPU (±4500 Events/s) and memory throughput (27,099.81 MB/s on average), and recorded the highest internal network speed of 52.8 Gbps. On the other hand, Proxmox showed dominance in disk I/O with achievements of up to 380 MiB/s and 97,000 operations per second, far surpassing OpenStack and OpenNebula which only recorded 40–45 MiB/s and ±11,000 ops/s. In a webload-based scalability test using Apache JMeter with 2000 users, Proxmox recorded the lowest error rate (9.5%) with an average response time of 7.2 seconds, while OpenNebula had the fastest response (6.4 seconds) but a higher error rate (15.5%), and OpenStack was in the middle with a response time of 7.6 seconds and an error rate of 14%. Based on overall results, OpenNebula is recommended for high-speed computing and networking needs, while Proxmox is better suited for large-scale environments that demand system stability and disk efficiency, and OpenStack can be considered as a balanced option between performance and stability.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Analisis Komparatif, Badan Informasi Geospasial, OpenNebula, OpenStack, Proxmox, Comparative Analysis, Geospatial Information Agency, OpenNebula, OpenStack, Proxmox
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T58.62 Decision support systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis
Depositing User:	Auditya Maulana Adnan
Date Deposited:	21 Jul 2025 01:36
Last Modified:	21 Jul 2025 01:56
URI:	http://repository.its.ac.id/id/eprint/120164

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