Fluentd brings records from multiple sources into a shared collection pipeline. Plugins read the inputs, parse and filter their contents, hold records temporarily when needed, and send them to the configured outputs. It is useful when different applications and destinations need a consistent logging path. The plugins are part of that design, so the exact image and configuration matter as much as the Fluentd core version.
Deployment and operating notes
The Fluent project publishes a current Fluentd chart, while Fluentd documentation defines collection, parsing, filtering, buffering and output behavior. The recovered plugin count and resource-use claims are dated marketing context, not a sizing result. A current core Fluentd release does not automatically make every community plugin or old container image compatible.
Build an inventory of the exact plugins, Ruby runtime, native dependencies and configuration used by the pipeline. Choose agent versus aggregator placement deliberately, and set storage and memory limits according to buffer peaks and destination outages. Test representative records from source to destination, including retries, malformed input and process restart. Review how secrets enter configuration and whether debug logs can reveal them. During a packaging change, preserve buffer and position-file semantics or document expected duplication. Keep the previous image and configuration until the replacement has passed a controlled outage test. Log collection is only one stage: retention, access controls and querying belong to the receiving system.
Historical upstream link check · 2026-10-09
The recorded upstream address responded successfully (HTTP 200) on 2026-10-09. Link availability does not certify the historical installation instructions or current security support.
Website availability is separate from project, chart and image support. Use the current guidance and primary sources on this page to assess the distribution.
Historical Kubedex content
Preserved for context. Commands, versions, prices and results below reflect the original research.
Fluentd is an open source data collector, which lets you unify the data collection and consumption for a better use and understanding of data.
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 (Unified Logging Layer). The downstream data processing is much easier with JSON, since it has enough structure to be accessible while retaining flexible schemas.
Pluggable Architecture
Fluentd has a flexible plugin system that allows the community to extend its functionality. Our 500+ community-contributed plugins connect dozens of data sources and data outputs. By leveraging the plugins, you can start making better use of your logs right away.
Minimum Resources Required
Fluentd is written in a combination of C language and Ruby, and requires very little system resource. The vanilla instance runs on 30-40MB of memory and can process 13,000 events/second/core. If you have tighter memory requirements (-450kb), check out Fluent Bit, the lightweight forwarder for Fluentd.
Built-in Reliability
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. 2,000+ data-driven companies rely on Fluentd to differentiate their products and services through a better use and understanding of their log data.
Sources & further reading
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