https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A comparative analysis of log management solutions: ELK stack versus PLG stack
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.
2023 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Managing and analyzing large volumes of logs can be challenging, and a log management solution can effectively address this issue. However, selecting the right log management solution can be a daunting task, considering various factors such as desired features and the solution's efficiency in terms of storage and resource usage. This thesis addressed the problem of choosing between two log management solutions: ELK and PLG. We compared their tailing agents, log storage and visualization capabilities to provide an analysis of their pros and cons. To compare the two log management solutions we conducted two types of evaluations: performance and functional evaluation. Together these two evaluations provide a comprehensive picture of each tool's capabilities. The study found that PLG is more resource-efficient in terms of CPU and memory compared to ELK, and requires less disk space to store logs. ELK, however, performs better in terms of query request time. ELK has a more user-friendly interface and requires minimal configuration, while PLG requires more configuration but provides more control for experienced users. With this study, we hope to provide organizations and individuals with a summary of the pros and cons of ELK and PLG that can help when choosing a log management solution.

Place, publisher, year, edition, pages
2023. , p. 49
Keywords [en]
ELK, PLG, Log management, Elasticsearch, Logstash, Kibana, Promtail, Loki, Grafana
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-63427OAI: oai:DiVA.org:mdh-63427DiVA, id: diva2:1771279
Subject / course
Computer Science
Supervisors
Examiners
Available from: 2023-06-21 Created: 2023-06-20 Last updated: 2025-10-10Bibliographically approved

Open Access in DiVA

ELK vs PLG(1520 kB)2865 downloads
File information
File name FULLTEXT01.pdfFile size 1520 kBChecksum SHA-512
f1609164b0ac4273b908b3d4afc9e43ebe71998a5a689274a8dac571ad0f098ff1945630512b0186b2e1718280da4a49c19d19c8d15246d0d1dacfb552d706af
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Eriksson, JoakimKaravek, Anawil
By organisation
School of Innovation, Design and Engineering
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 2867 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 2980 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf