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・ "Our Contemporary" regional art exhibition (Leningrad, 1975)
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・ "R" The King (2016 film)
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・ ! (disambiguation)
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・ !!Destroy-Oh-Boy!!
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・ !Hero
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・ !Kung language
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・ !Women Art Revolution


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Hiro Yoshikawa : ウィキペディア英語版
Fluentd

Fluentd is a cross platform open source data collection software originally developed at Treasure Data. It is written primarily in Ruby.
== Overview ==
Fluentd is an open source data collector to unify logging infrastructure. Unlike traditional logging tools like syslogd, it has four key properties:
* Unified Logging with JSON: Fluentd tries to structure data as JSON as much as possible. This allows Fluentd to unify all facets of processing log data: collecting, filtering, buffering, and outputting logs across multiple sources and destinations. The downstream data processing is much easier with JSON, since it has enough structure to be accessible without forcing rigid schemas.〔https://www.pandastrike.com/posts/20150807-fluentd-vs-logstash〕
* Pluggable Architecture: Fluentd has a flexible plugin system that allows the community to extend its functionality. The 300+ community-contributed plugins connect dozens of data sources to dozens of data outputs, manipulating the data as needed. By using plugins, you can make better use of your logs right away.〔https://github.com/fluent/fluentd〕
* Minimal Resources Required: A data collector ought to be lightweight so that the user can run it comfortably on a busy machine. Fluentd is written in a combination of C and Ruby, and requires minimal system resources. The vanilla instance runs on 30-40MB of memory and can process 13,000 events/second/core.〔http://www.quora.com/What-is-Fluentd-1〕
* Built-in Reliability: Data loss should never happen. Fluentd supports memory- and file-based buffering to prevent inter-node data loss. Fluentd also supports robust failover and can be set up for high availability.〔https://www.datadoghq.com/blog/monitor-fluentd-datadog/〕
Fluentd tries to structure data as JSON as much as possible: this allows Fluentd to unify all facets of processing log data: collecting, filtering, buffering, and outputting logs across multiple sources and destinations (Unified Logging Layer). The downstream data processing is much easier with JSON, since it has enough structure to be accessible while retaining flexible schemas.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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