Fluent Bit: Official Manual
SlackGitHubCommunity MeetingsSandbox and LabsWebinars
1.3
1.3
  • Introduction
  • About
    • Why ?
    • Fluentd & Fluent Bit
    • License
  • Installation
    • Supported Platforms
    • Requirements
    • Download Sources
    • Upgrade Notes
    • Build and Install
    • Build with Static Configuration
    • Docker Images
    • Kubernetes
    • TD Agent Bit
    • Debian Packages
    • Ubuntu Packages
    • CentOS Packages
    • Raspberry Pi
    • Yocto Project
    • Windows
  • Getting Started
    • Service
    • Input
    • Parser
    • Filter
    • Buffer
    • Routing
    • Output
  • Configuration
    • Configuration Schema
    • Configuration File
    • Configuration Variables
    • Configuration Commands
    • Buffering / Storage
    • Monitoring
    • Unit Sizes
    • TLS / SSL
    • Backpressure
    • Memory Usage
    • Upstream Servers
    • Scheduler
    • Stream Processor
  • Service
  • Input Plugins
    • Collectd
    • CPU Usage
    • Disk Usage
    • Dummy
    • Exec
    • Forward
    • Head
    • Health
    • Kernel Log Buffer
    • Memory Usage
    • MQTT
    • Network Traffic
    • Process
    • Random
    • Serial Interface
    • Standard Input
    • Syslog
    • Systemd
    • Tail
    • TCP
    • Thermal
    • Windows Event Log
  • Parsers
    • JSON Parser
    • Regular Expression Parser
    • LTSV Parser
    • Logfmt Parser
    • Decoders
  • Filter Plugins
    • Grep
    • Kubernetes
    • Lua
    • Parser
    • Record Modifier
    • Standard Output
    • Throttle
    • Nest
    • Modify
  • Output Plugins
    • Azure
    • BigQuery
    • Counter
    • Datadog
    • Elasticsearch
    • File
    • FlowCounter
    • Forward
    • GELF
    • HTTP
    • InfluxDB
    • Kafka
    • Kafka REST Proxy
    • NATS
    • Null
    • Stackdriver
    • Standard Output
    • Splunk
    • TCP & TLS
    • Treasure Data
  • Fluent Bit for Developers
    • Library API
    • Ingest Records Manually
    • Fluent Bit and Golang Plugins
Powered by GitBook
On this page
  • Configuration Parameters
  • Functional description
  • Interval vs Window size
  • Command Line
  • Configuration File

Was this helpful?

Export as PDF
  1. Filter Plugins

Throttle

The Throttle Filter plugin sets the average Rate of messages per Interval, based on leaky bucket and sliding window algorithm. In case of overflood, it will leak within certain rate.

Configuration Parameters

The plugin supports the following configuration parameters:

Key

Value Format

Description

Rate

Integer

Amount of messages for the time.

Window

Integer

Amount of intervals to calculate average over. Default 5.

Interval

String

Time interval, expressed in "sleep" format. e.g 3s, 1.5m, 0.5h etc

Print_Status

Bool

Whether to print status messages with current rate and the limits to information logs

Functional description

Lets imagine we have configured:

Rate 5
Window 5
Interval 1s

we received 1 message first second, 3 messages 2nd, and 5 3rd. As you can see, disregard that Window is actually 5, we use "slow" start to prevent overflooding during the startup.

+-------+-+-+-+ 
|1|3|5| | | | | 
+-------+-+-+-+ 
|  3  |         average = 3, and not 1.8 if you calculate 0 for last 2 panes. 
+-----+

But as soon as we reached Window size * Interval, we will have true sliding window with aggregation over complete window.

+-------------+ 
|1|3|5|7|3|4| | 
+-------------+ 
  |  4.4    |   
  ----------+

When we have average over window is more than Rate, we will start dropping messages, so that

+-------------+
|1|3|5|7|3|4|7|
+-------------+
    |   5.2   |
    +---------+

will become:

+-------------+
|1|3|5|7|3|4|6|
+-------------+
    |   5     |
    +---------+

As you can see, last pane of the window was overwritten and 1 message was dropped.

Interval vs Window size

You might noticed possibility to configure Interval of the Window shift. It is counter intuitive, but there is a difference between two examples above:

Rate 60
Window 5
Interval 1m

and

Rate 1
Window 300
Interval 1s

Even though both examples will allow maximum Rate of 60 messages per minute, first example may get all 60 messages within first second, and will drop all the rest for the entire minute:

XX        XX        XX
XX        XX        XX
XX        XX        XX
XX        XX        XX
XX        XX        XX
XX        XX        XX
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

While the second example will not allow more than 1 message per second every second, making output rate more smooth:

  X    X     X    X    X    X
XXXX XXXX  XXXX XXXX XXXX XXXX
+-+-+-+-+-+--+-+-+-+-+-+-+-+-+-+

It may drop some data if the rate is ragged. I would recommend to use bigger interval and rate for streams of rare but important events, while keep Window bigger and Interval small for constantly intensive inputs.

Command Line

Note: It's suggested to use a configuration file.

The following command will load the tail plugin and read the content of lines.txt file. Then the throttle filter will apply a rate limit and only pass the records which are read below the certain rate:

$ bin/fluent-bit -i tail -p 'path=lines.txt' -F throttle -p 'rate=1' -m '*' -o stdout

Configuration File

[INPUT]
    Name   tail
    Path   lines.txt

[FILTER]
    Name     throttle
    Match    *
    Rate     1000
    Window   300
    Interval 1s

[OUTPUT]
    Name   stdout
    Match  *

The example above will pass 1000 messages per second in average over 300 seconds.

Last updated 5 years ago

Was this helpful?