Fluentd
| Developer(s) | Treasure Data |
|---|---|
| Initial release | 10 October 2011; 13 years ago (2011年10月10日) |
| Stable release | |
| Repository | |
| Written in | C, Ruby |
| Operating system | Linux (Amazon Linux, CentOS, RHEL), macOS (10.9 and above), Windows (7 and above) |
| Type | Logging tool |
| License | Apache 2.0 |
| Website | www |
Fluentd is a cross-platform open-source data collection software project originally developed at Treasure Data. It is written primarily in the C programming language with a thin-Ruby wrapper that gives users flexibility.[2]
Overview
[edit ]Fluentd was positioned for "big data," semi- or un-structured data sets. It analyzes event logs, application logs, and clickstreams.[3] According to Suonsyrjä and Mikkonen, the "core idea of Fluentd is to be the unifying layer between different types of log inputs and outputs.",[4] Fluentd is available on Linux, macOS, and Windows.[5]
History
[edit ]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.[6] [7] The company announced 5ドル million of funding in 2013.[8] Treasure Data was then sold to Arm Ltd. in 2018.[9]
Users
[edit ]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.[10] 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-fluent, as a default logging agent.[11] [12]
Fluent Bit
[edit ]Fluent Bit is a log processor and log forwarder that is being developed as a CNCF sub-project under the umbrella of Fluent project.[13] Fluentd is written in C and Ruby and consumes at least 60 megabytes of memory. Fluent Bit is written only in C, with no dependencies, and consumes approximately one megabyte of memory, making it easier to run under embedded Linux and in containers.[14]
References
[edit ]- ^ "Releases - fluent/fluentd" – via GitHub.
- ^ https://docs.fluentd.org/quickstart [bare URL ]
- ^ Pasupuleti, Pradeep and Purra, Beulah Salome (2015). Data Lake Development with Big Data. pp. 44–45; 48. Packt. ISBN 1785881663
- ^ Suonsyrjä, Sampo and Mikkonen, Tommi "Designing an Unobtrusive Analytics Framework for Monitoring Java Applications", pp. 170–173 in Software Measurement. Springer. ISBN 3319242857
- ^ Fluentd.org. "Download Fluentd". Retrieved 10 March 2016.
- ^ Mayer, Chris (30 October 2013). "Treasure Data: Breaking down the Hadoop barrier". JAXenter
- ^ Fluentd.org. "What is Fluentd?". Retrieved 10 March 2016.
- ^ Derrick Harris (July 23, 2013). "Treasure Data raises 5ドルM, fuses Hadoop and data warehouse in Amazon's cloud". GigaOm.
- ^ "Arm unit Treasure Data to seek buyer or IPO before Nvidia sale". Nikkei Asia. November 19, 2020. Retrieved August 2, 2021.
- ^ Parviz Deyhim (August 2013). "Best Practices for Amazon EMR" (PDF). Amazon Web Services. p. 12. Archived from the original (PDF) on 2016年03月26日. Retrieved March 24, 2017.
- ^ Google Cloud Platform (2016). "Real-time logs analysis using Fluentd and BigQuery". Retrieved 10 March 2016.
- ^ Google Cloud Platform (2016). "The Logging Agent". Retrieved 10 March 2016.
- ^ "Fluent Bit". fluentbit.io. Retrieved 2021年12月05日.
- ^ "Fluentd & Fluent Bit - Fluent Bit: Official Manual" . Retrieved 2021年12月05日.
Further reading
[edit ]- Goasguen, Sébastien (2014). 60 Recipes for Apache CloudStack: Using the CloudStack Ecosystem, "Chapter 6: Advanced Recipes". O'Reilly Media. ISBN 1491910127
- Wilkins, Phil (2022). Logging in Action, With Fluentd, Kubernetes and more. Manning. ISBN 9781617298356