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
    • License
    • Sandbox and Lab Resources
  • Concepts
    • Key Concepts
    • Buffering
    • Data Pipeline
      • Input
      • Parser
      • Filter
      • Buffer
      • Router
      • Output
  • Installation
    • Getting Started with Fluent Bit
    • Upgrade Notes
    • Supported Platforms
    • Requirements
    • Sources
      • Download Source Code
      • Build and Install
      • Build with Static Configuration
    • Linux Packages
      • Amazon Linux
      • Redhat / CentOS
      • Debian
      • Ubuntu
      • Raspbian / Raspberry Pi
    • Docker
    • Containers on AWS
    • Amazon EC2
    • Kubernetes
    • macOS
    • Windows
    • Yocto / Embedded Linux
    • Buildroot / Embedded Linux
  • Administration
    • Configuring Fluent Bit
      • YAML Configuration
        • Service
        • Parsers
        • Multiline Parsers
        • Pipeline
        • Plugins
        • Upstream Servers
        • Environment Variables
        • Includes
      • Classic mode
        • Format and Schema
        • Configuration File
        • Variables
        • Commands
        • Upstream Servers
        • Record Accessor
      • Unit Sizes
      • Multiline Parsing
    • Transport Security
    • Buffering and Storage
    • Backpressure
    • Scheduling and Retries
    • Networking
    • Memory Management
    • Monitoring
    • Multithreading
    • HTTP Proxy
    • Hot Reload
    • Troubleshooting
    • Performance Tips
    • AWS credentials
  • Local Testing
    • Validating your Data and Structure
    • Running a Logging Pipeline Locally
  • Data Pipeline
    • Pipeline Monitoring
    • Inputs
      • Collectd
      • CPU Log Based Metrics
      • Disk I/O Log Based Metrics
      • Docker Events
      • Docker Log Based Metrics
      • Dummy
      • Elasticsearch
      • Exec
      • Exec Wasi
      • Ebpf
      • Fluent Bit Metrics
      • Forward
      • Head
      • Health
      • HTTP
      • Kafka
      • Kernel Logs
      • Kubernetes Events
      • Memory Metrics
      • MQTT
      • Network I/O Log Based Metrics
      • NGINX Exporter Metrics
      • Node Exporter Metrics
      • OpenTelemetry
      • Podman Metrics
      • Process Exporter Metrics
      • Process Log Based Metrics
      • Prometheus Remote Write
      • Prometheus Scrape Metrics
      • Random
      • Serial Interface
      • Splunk
      • Standard Input
      • StatsD
      • Syslog
      • Systemd
      • Tail
      • TCP
      • Thermal
      • UDP
      • Windows Event Log
      • Windows Event Log (winevtlog)
      • Windows Exporter Metrics
    • Parsers
      • Configuring Parser
      • JSON
      • Regular Expression
      • LTSV
      • Logfmt
      • Decoders
    • Processors
      • Content Modifier
      • Labels
      • Metrics Selector
      • OpenTelemetry Envelope
      • Sampling
      • SQL
      • Filters as processors
      • Conditional processing
    • Filters
      • AWS Metadata
      • CheckList
      • ECS Metadata
      • Expect
      • GeoIP2 Filter
      • Grep
      • Kubernetes
      • Log to Metrics
      • Lua
      • Parser
      • Record Modifier
      • Modify
      • Multiline
      • Nest
      • Nightfall
      • Rewrite Tag
      • Standard Output
      • Sysinfo
      • Throttle
      • Type Converter
      • Tensorflow
      • Wasm
    • Outputs
      • Amazon CloudWatch
      • Amazon Kinesis Data Firehose
      • Amazon Kinesis Data Streams
      • Amazon S3
      • Azure Blob
      • Azure Data Explorer
      • Azure Log Analytics
      • Azure Logs Ingestion API
      • Counter
      • Dash0
      • Datadog
      • Dynatrace
      • Elasticsearch
      • File
      • FlowCounter
      • Forward
      • GELF
      • Google Chronicle
      • Google Cloud BigQuery
      • HTTP
      • InfluxDB
      • Kafka
      • 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
      • Splunk
      • 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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  • Fluent Bit data pipeline
  • Stream processor

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  1. Stream Processing

Overview

Last updated 1 month ago

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Stream processing is a feature that lets you query continuous data streams while they're still in motion. Fluent Bit uses a streaming SQL engine for this process.

To understand how stream processing works in Fluent Bit, follow this overview of Fluent Bit architecture and how data travels through the pipeline.

Fluent Bit data pipeline

collects and process logs (also known as records) from different input sources, then parses and filters these records before they're stored. After data is processed and in a safe state, meaning either in memory or in the file system, the records are routed through the proper output destinations.

Most of the phases in the pipeline are implemented through plugins: input, filter, and output.

Filters can perform specific record modifications like appending or removing a key, enriching with metadata (for example, Kubernetes filter), or discarding records based on specific conditions. After data is stored, no further modifications are made, but records can optionally be redirected to the stream processor.

Stream processor

The stream processor is an independent subsystem that checks for new records hitting the storage interface. Based on your configuration settings, the stream processor will attach to records that come from a specific input plugin or by applying tag and matching rules.

Every input instance is considered a stream. These streams collect data and ingest records into the pipeline.

By configuring specific SQL queries, you can perform specific tasks like key selections, filtering, and data aggregation. Keep in mind that there is no database; everything is schema-less and happens in memory. Concepts like tables that are common in relational database don't exist in Fluent Bit.

One powerful feature of the Fluent Bit stream processor is the ability to create new streams of data using the results from a previous SQL query. These results are re-ingested back into the pipeline to be consumed again for the stream processor, if desired, or routed to output destinations by any common record using tag/matching rules. (Stream processor results can be tagged.)

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