Fluent Bit: Official Manual
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4.0
4.0
  • 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
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      • Redhat / CentOS
      • Debian
      • Ubuntu
      • Raspbian / Raspberry Pi
    • Docker
    • Containers on AWS
    • Amazon EC2
    • Kubernetes
    • macOS
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    • Buildroot / Embedded Linux
  • Administration
    • Configuring Fluent Bit
      • YAML Configuration
        • Service
        • Parsers
        • Multiline Parsers
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        • Includes
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    • HTTP Proxy
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    • AWS credentials
  • Local Testing
    • Validating your Data and Structure
    • Running a Logging Pipeline Locally
  • Data Pipeline
    • Pipeline Monitoring
    • Inputs
      • Collectd
      • CPU Log Based Metrics
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      • Docker Events
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      • Forward
      • Head
      • Health
      • HTTP
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      • MQTT
      • Network I/O Log Based Metrics
      • NGINX Exporter Metrics
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      • OpenTelemetry
      • Podman Metrics
      • Process Exporter Metrics
      • Process Log Based Metrics
      • Prometheus Remote Write
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      • Splunk
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      • StatsD
      • Syslog
      • Systemd
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      • TCP
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      • Windows Event Log
      • Windows Event Log (winevtlog)
      • Windows Exporter Metrics
    • Parsers
      • Configuring Parser
      • JSON
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    • Processors
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      • Labels
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      • Conditional processing
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      • AWS Metadata
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      • Kubernetes
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      • Modify
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    • Outputs
      • Amazon CloudWatch
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      • Amazon S3
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      • Azure Logs Ingestion API
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      • File
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      • 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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  1. Concepts
  2. Data Pipeline

Parser

Convert unstructured messages to structured messages

Last updated 1 month ago

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Dealing with raw strings or unstructured messages is difficult. Having a structure makes data more usable. Set a structure to the incoming data by using input plugins as data is collected:

The parser converts unstructured data to structured data. As an example, consider the following Apache (HTTP Server) log entry:

192.168.2.20 - - [28/Jul/2006:10:27:10 -0300] "GET /cgi-bin/try/ HTTP/1.0" 200 3395

This log line is a raw string without format. Structuring the log makes it easier to process the data later. If the is used, the log entry could be converted to:

{
  "host":    "192.168.2.20",
  "user":    "-",
  "method":  "GET",
  "path":    "/cgi-bin/try/",
  "code":    "200",
  "size":    "3395",
  "referer": "",
  "agent":   ""
 }

Parsers are fully configurable and are independently and optionally handled by each input plugin. For more details, see.

regular expression parser
Parsers