Fluent Bit: Official Manual
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  • Fluent Bit Documentation
  • About
    • What is Fluent Bit?
    • A Brief History of Fluent Bit
    • Fluentd and Fluent Bit
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  • Concepts
    • Key Concepts
    • Buffering
    • Data Pipeline
      • Input
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  • Administration
    • Configuring Fluent Bit
      • YAML Configuration
        • Service
        • Parsers
        • Multiline Parsers
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        • Includes
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    • Validating your Data and Structure
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      • Forward
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      • NGINX Exporter Metrics
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      • OpenTelemetry
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      • Process Log Based Metrics
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      • Windows Event Log
      • Windows Event Log (winevtlog)
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      • Configuring Parser
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    • Outputs
      • Amazon CloudWatch
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      • FlowCounter
      • Forward
      • GELF
      • Google Chronicle
      • Google Cloud BigQuery
      • HTTP
      • InfluxDB
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      • Kafka REST Proxy
      • LogDNA
      • Loki
      • Microsoft Fabric
      • NATS
      • New Relic
      • NULL
      • Observe
      • OpenObserve
      • OpenSearch
      • OpenTelemetry
      • Oracle Log Analytics
      • PostgreSQL
      • Prometheus Exporter
      • Prometheus Remote Write
      • SkyWalking
      • Slack
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      • Stackdriver
      • Standard Output
      • Syslog
      • TCP and TLS
      • Treasure Data
      • Vivo Exporter
      • WebSocket
  • Stream Processing
    • Introduction to Stream Processing
    • Overview
    • Changelog
    • Getting Started
      • Fluent Bit + SQL
      • Check Keys and NULL values
      • Hands On 101
  • Fluent Bit for Developers
    • C Library API
    • Ingest Records Manually
    • Golang Output Plugins
    • WASM Filter Plugins
    • WASM Input Plugins
    • Developer guide for beginners on contributing to Fluent Bit
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  1. Administration

Multithreading

Learn how to run Fluent Bit in multiple threads for improved scalability.

Last updated 1 month ago

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Fluent Bit has one event loop to handle critical operations, like managing timers, receiving internal messages, scheduling flushes, and handling retries. This event loop runs in the main Fluent Bit thread.

To free up resources in the main thread, you can configure and to run in their own self-contained threads. However, inputs and outputs implement multithreading in distinct ways: inputs can run in threaded mode, and outputs can use one or more workers.

Threading also affects certain processes related to inputs and outputs. For example, always run in the main thread, but run in the self-contained threads of their respective inputs or outputs, if applicable.

Inputs

When inputs collect telemetry data, they can either perform this process inside the main Fluent Bit thread or inside a separate dedicated thread. You can configure this behavior by enabling or disabling the threaded setting.

All inputs are capable of running in threaded mode, but certain inputs always run in threaded mode regardless of configuration. These always-threaded inputs are:

Inputs aren't internally aware of multithreading. If an input runs in threaded mode, Fluent Bit manages the logistics of that input's thread.

Outputs

When outputs flush data, they can either perform this operation inside Fluent Bit's main thread or inside a separate dedicated thread called a worker. Each output can have one or more workers running in parallel, and each worker can handle multiple concurrent flushes. You can configure this behavior by changing the value of theworkers setting.

All outputs are capable of running in multiple workers, and each output has a default value of 0, 1, or 2 workers. However, even if an output uses workers by default, you can safely reduce the number of workers below the default or disable workers entirely.

inputs
outputs
filters
processors
Kubernetes Events
Node Exporter Metrics
Process Exporter Metrics
Windows Exporter Metrics