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Open access Journal SINTA 2

Optimizing Virtual Resources Management Using Docker on Cloud Applications

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 14 No. 3 (2020) · pp. 319–330

DOI
10.22146/ijccs.57565
ISSN
2460-7258, 1978-1520
Published
2020-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.

Keywords

Collaboration network of the authors

18 authors · 41 co-authorship links · 1 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Narotama
  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Sayid Fariz Bin Seh AbubakarAffiliation unknown2
Muhammad MuhibbiAffiliation unknown2
Ahad Agafian DhuhaAffiliation unknown2
Andre YogaswaraAffiliation unknown2
Indar SugiartoAffiliation unknown2
Astri YogatamaAffiliation unknown2
Frismanda FrismandaAffiliation unknown2
Achmad Holil Noor AliInstitut Teknologi Sepuluh Nopember1
Vani Dias AdiprabowoAffiliation unknown1
Ari AndayaniAffiliation unknown1
Ariesanti Tri HandayaniAffiliation unknown1
Kevin HendrawanAffiliation unknown1
Ernawati TitiekAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Oct 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Optimizing Virtual Resources Management Using Docker on Cloud Applications</dc:title>
	<dc:creator>Felani, Rendra</dc:creator>
	<dc:creator>Al Azam, Moh Noor</dc:creator>
	<dc:creator>Adi, Derry Pramono</dc:creator>
	<dc:creator>Widodo, Agung</dc:creator>
	<dc:creator>Gumelar, Agustinus Bimo</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">CaaS; Container; Docker; Virtualization</dc:subject>
	<dc:description xml:lang="en-US">This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2020-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/57565</dc:identifier>
	<dc:identifier>10.22146/ijccs.57565</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 319-330</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/57565/28384</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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