Fluentd

Fluentd is a cross-platform open-source data collection software project originally developed at Treasure Data. It is written primarily in the Ruby programming language.

Fluentd
Developer(s)Treasure Data
Initial release10 October 2011 (2011-10-10)
Stable release
1.15.3 / November 2, 2022 (2022-11-02)[1]
Repository
Written inC, Ruby
Operating systemLinux (Amazon Linux, CentOS, RHEL), macOS (10.9 and above), Ruby, Windows (7 and above)
TypeLogging tool
LicenseApache 2.0
Websitewww.fluentd.org

Overview

Fluentd was positioned for "big data", semi- or un-structured data sets. It analyzes event logs, application logs, and clickstreams.[2] According to Suonsyrjä and Mikkonen, the "core idea of Fluentd is to be the unifying layer between different types of log inputs and outputs.",[3] Fluentd is available on Linux, macOS, and Windows.[4]

History

Fluentd was created by Sadayuki Furuhashi as a project of the Mountain View-based firm Treasure Data. Written primarily in Ruby, its source code was released as open-source software in October 2011.[5][6] The company announced $5 million of funding in 2013.[7] Treasure Data was then sold to Arm Ltd. in 2018.[8]

Users

Fluentd was one of the data collection tools recommended by Amazon Web Services in 2013, when it was said to be similar to Apache Flume or Scribe.[9] Google Cloud Platform's BigQuery recommends Fluentd as the default real-time data-ingestion tool, and uses Google's customized version of Fluentd, called google-fluentd, as a default logging agent.[10][11]

Fluent Bit

Fluent Bit is a log processor and log forwarder which is being developed as a CNCF sub-project under the umbrella of Fluentd project.[12] Fluentd is written in C and Ruby and built as a Ruby gem so it consumes some amount of memory resources. On the other hand, since Fluent Bit is written only in C and has no dependencies, the consumed memory usage much decreased compared to Fluentd which makes it easy to run on the embedded Linux and container environment.[13]

References
  1. "Releases - fluent/fluentd" – via GitHub.
  2. Pasupuleti, Pradeep and Purra, Beulah Salome (2015). Data Lake Development with Big Data. pp. 44–45; 48. Packt. ISBN 1785881663
  3. Suonsyrjä, Sampo and Mikkonen, Tommi "Designing an Unobtrusive Analytics Framework for Monitoring Java Applications", pp. 170–173 in Software Measurement. Springer. ISBN 3319242857
  4. Fluentd.org. "Download Fluentd". Retrieved 10 March 2016.
  5. Mayer, Chris (30 October 2013). "Treasure Data: Breaking down the Hadoop barrier". JAXenter
  6. Fluentd.org. "What is Fluentd?". Retrieved 10 March 2016.
  7. Derrick Harris (July 23, 2013). "Treasure Data raises $5M, fuses Hadoop and data warehouse in Amazon's cloud". GigaOm.
  8. "Arm unit Treasure Data to seek buyer or IPO before Nvidia sale". Nikkei Asia. November 19, 2020. Retrieved August 2, 2021.
  9. Parviz Deyhim (August 2013). "Best Practices for Amazon EMR" (PDF). Amazon Web Services. p. 12. Archived from the original (PDF) on 2016-03-26. Retrieved March 24, 2017.
  10. Google Cloud Platform (2016). "Real-time logs analysis using Fluentd and BigQuery". Retrieved 10 March 2016.
  11. Google Cloud Platform (2016). "The Logging Agent". Retrieved 10 March 2016.
  12. "Fluent Bit". fluentbit.io. Retrieved 2021-12-05.
  13. "Fluentd & Fluent Bit - Fluent Bit: Official Manual". Retrieved 2021-12-05.

Further reading
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