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Aggregated Containerized Logging Solution with Fluentd, Elasticsearch and Kibana

by Kaichuang Yang
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 150 - Number 3
Year of Publication: 2016
Authors: Kaichuang Yang
10.5120/ijca2016911479

Kaichuang Yang . Aggregated Containerized Logging Solution with Fluentd, Elasticsearch and Kibana. International Journal of Computer Applications. 150, 3 ( Sep 2016), 29-31. DOI=10.5120/ijca2016911479

@article{ 10.5120/ijca2016911479,
author = { Kaichuang Yang },
title = { Aggregated Containerized Logging Solution with Fluentd, Elasticsearch and Kibana },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 150 },
number = { 3 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 29-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume150/number3/26076-2016911479/ },
doi = { 10.5120/ijca2016911479 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:54:56.945391+05:30
%A Kaichuang Yang
%T Aggregated Containerized Logging Solution with Fluentd, Elasticsearch and Kibana
%J International Journal of Computer Applications
%@ 0975-8887
%V 150
%N 3
%P 29-31
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the operation and maintenance of cloud production lines, access to logs from containers in order to perform day-to-day investigation and debugging is needed. Logs must be accessible beyond the life of a container. Logs from across the cluster need to be aggregated to allow log searching, backup, and storage. As a solution, this paper present a diagram combined with Fluentd, Elasticsearch and Kibana, that enables the deployment and management of multiple containers log reviewing with a creatively way. The solution perform well efficiently on log collection and indexing. Even though the prototype has been effectively used to deploy and manage containers logging data, serial risks are still needed put into consideration as important issues.

References
  1. T. Prakash, M. Kakkar and K. Patel, "Geo-identification of web users through logs using ELK stack," 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence), Noida, 2016, pp. 606-610.
  2. P. P. I. Langi, Widyawan, W. Najib and T. B. Aji, "An evaluation of Twitter river and Logstash performances as elasticsearch inputs for social media analysis of Twitter," Information & Communication Technology and Systems (ICTS), 2015 International Conference on, Surabaya, 2015, pp. 181-186.
  3. W. Wongthai, F. Rocha and A. v. Moorsel, "Logging Solutions to Mitigate Risks Associated with Threats in Infrastructure as a Service Cloud," Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on, Fuzhou, 2013, pp. 163-170.
  4. Logging Evaluation of the Ordovician Carbonate Reservoir Beds in the Lungudong Region, Tarim Basin [J]. Acta Geologica Sinica (English Edition), 2010, 05:1141-1156.
  5. Effects of electric-acoustic and acoustic-electric conversions of transducers on acoustic logging signal [J]. Chinese Science Bulletin, 2012, 11:1246-1260.
Index Terms

Computer Science
Information Sciences

Keywords

Logging solution Fluentd Elasticsearch Kibana Proxy Performance testing.

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