Before diving into Fluent Bit it’s good to get acquainted with some of the key concepts of the service. This document provides a gentle introduction to those concepts and common Fluent Bit terminology. We’ve provided a list below of all the terms we’ll cover, but we recommend reading this document from start to finish to gain a more general understanding of our log and stream processor.

• Event or Record

• Filtering

• Tag

• Timestamp

• Match

• Structured Message

Event or Record

Every incoming piece of data that belongs to a log or a metric that is retrieved by Fluent Bit is considered an Event or a Record.

As an example consider the following content of a Syslog file:

Jan 18 12:52:16 flb systemd[2222]: Starting GNOME Terminal Server
Jan 18 12:52:16 flb dbus-daemon[2243]: [session uid=1000 pid=2243] Successfully activated service 'org.gnome.Terminal'
Jan 18 12:52:16 flb systemd[2222]: Started GNOME Terminal Server.
Jan 18 12:52:16 flb gsd-media-keys[2640]: # watch_fast: "/org/gnome/terminal/legacy/" (establishing: 0, active: 0)

It contains four lines and all of them represents four independent Events.

Internally, an Event always has two components (in an array form):

[TIMESTAMP, MESSAGE]

Filtering

In some cases is required to perform modifications on the Events content, the process to alter, enrich or drop Events is called Filtering.

There are many use cases when Filtering is required like:

• Append specific information to the Event like an IP address or metadata.

• Select a specific piece of the Event content.

• Drop Events that matches certain pattern.

Tag

Every Event that gets into Fluent Bit gets assigned a Tag. This tag is an internal string that is used in a later stage by the Router to decide which Filter or Output phase it must go through.

Most of the tags are assigned manually in the configuration. If a tag is not specified, Fluent Bit will assign the name of the Input plugin instance from where that Event was generated from.

A Tagged record must always have a Matching rule. To learn more about Tags and Matches check the Routing section.

Timestamp

The Timestamp represents the time when an Event was created. Every Event contains a Timestamp associated. The Timestamp is a numeric fractional integer in the format:

SECONDS.NANOSECONDS

Seconds

It is the number of seconds that have elapsed since the Unix epoch.

Nanoseconds

Fractional second or one thousand-millionth of a second.

Match

Fluent Bit allows to deliver your collected and processed Events to one or multiple destinations, this is done through a routing phase. A Match represent a simple rule to select Events where it Tags matches a defined rule.

To learn more about Tags and Matches check the Routing section.

Structured Messages

Source events can have or not have a structure. A structure defines a set of keys and values inside the Event message. As an example consider the following two messages:

No structured message

"Project Fluent Bit created on 1398289291"

Structured Message

{"project": "Fluent Bit", "created": 1398289291}

At a low level both are just an array of bytes, but the Structured message defines keys and values, having a structure helps to implement faster operations on data modifications.

When Fluent Bit process data, it uses the system memory (heap) as a primary and temporal place to store the record logs before they get delivered, on this private memory area the records are processed.

Buffering refers to the ability to store the records somewhere, and while they are processed and delivered, still be able to store more. Buffering in memory is the fastest mechanism, but there are certain scenarios where the mechanism requires special strategies to deal with backpressure, data safety or reduce memory consumption by the service in constraint environments.

Fluent Bit as buffering strategies, offers a primary buffering mechanism in memory and an optional secondary one using the file system. With this hybrid solution you can adjust to any use case safety and keep a high performance while processing your data.

Both mechanisms are not exclusive and when the data is ready to be processed or delivered it will be always in memory, while other data in the queue might be in the file system until is ready to be processed and moved up to memory.

To learn more about the buffering configuration in Fluent Bit, please jump to the Buffering & Storage section.

On 2014, the Fluentd team at Treasure Data forecasted the need of a lightweight log processor for constraint environments like Embedded Linux and Gateways, the project aimed to be part of the Fluentd Ecosystem and we called it Fluent Bit, fully open source and available under the terms of the Apache License v2.0.

After the project was around for some time, it got some traction in the Embedded market but we also started getting requests for several features from the Cloud community like more inputs, filters, and outputs. Not so long after that, Fluent Bit becomes one of the preferred solutions to solve the logging challenges in Cloud environments.

Logging and data processing in general can be complex, and at scale a bit more, that's why Fluentd was born. But now is more than a simple tool, it's a full ecosystem that contains SDKs for different languages and sub projects like Fluent Bit.

On this page, we will describe the relationship between the Fluentd and Fluent Bit open source projects, as a summary we can say both are:

• Licensed under the terms of Apache License v2.0

• Hosted projects by the Cloud Native Computing Foundation (CNCF)

• Production Grade solutions: deployed thousands of times every single day, millions per month.

• Community driven projects

• Widely Adopted by the Industry: trusted by all major companies like AWS, Microsoft, Google Cloud and hundred of others.

• Originally created by Treasure Data.

Both projects share a lot of similarities, Fluent Bit is fully designed and built on top of the best ideas of Fluentd architecture and general design. Choosing which one to use depends on the end-user needs.

The following table describes a comparison in different areas of the projects:

Both Fluentd and Fluent Bit can work as Aggregators or Forwarders, they both can complement each other or use them as standalone solutions.

Previously defined in the concept section, the buffer phase in the pipeline aims to provide a unified and persistent mechanism to store your data, either using the primary in-memory model or using the filesystem based mode.

The buffer phase already contains the data in an immutable state, meaning, no other filter can be applied.

Fluent Bit offers a buffering mechanism in the file system that acts as a backup system to avoid data loss in case of system failures.

, including it core, plugins and tools are distributed under the terms of the :

The following article cover the relevant notes for users upgrading from previous Fluent Bit versions. We aim to cover compatibility changes that you must be aware of.

For more details about changes on each release please refer to the Official Release Notes.

Fluent Bit v1.4

If you are migrating from Fluent Bit v1.3, there are not breaking changes. Just new exciting features to enjoy :)

Fluent Bit v1.3

If you are migrating from Fluent Bit v1.2 to v1.3, there are not breaking changes. If you are upgrading from an older version please review the incremental changes below.

Fluent Bit v1.2

Docker, JSON, Parsers and Decoders

On Fluent Bit v1.2 we have fixed many issues associated with JSON encoding and decoding, for hence when parsing Docker logs is no longer necessary to use decoders. The new Docker parser looks like this:

[PARSER]
    Name         docker
    Format       json
    Time_Key     time
    Time_Format  %Y-%m-%dT%H:%M:%S.%L
    Time_Keep    On

Note: again, do not use decoders.

Kubernetes Filter

We have done improvements also on how Kubernetes Filter handle the stringified log message. If the option Merge_Log is enabled, it will try to handle the log content as a JSON map, if so, it will add the keys to the root map.

In addition, we have fixed and improved the option called Merge_Log_Key. If a merge log succeed, all new keys will be packaged under the key specified by this option, a suggested configuration is as follows:

[FILTER]
    Name             Kubernetes
    Match            kube.*
    Kube_Tag_Prefix  kube.var.log.containers.
    Merge_Log        On
    Merge_Log_Key    log_processed

As an example, if the original log content is the following map:

{"key1": "val1", "key2": "val2"}

the final record will be composed as follows:

{
    "log": "{\"key1\": \"val1\", \"key2\": \"val2\"}",
    "log_processed": {
        "key1": "val1",
        "key2": "val2"
    }
}

Fluent Bit v1.1

If you are upgrading from Fluent Bit <= 1.0.x you should take in consideration the following relevant changes when switching to Fluent Bit v1.1 series:

Kubernetes Filter

We introduced a new configuration property called Kube_Tag_Prefix to help Tag prefix resolution and address an unexpected behavior that landed in previous versions.

During 1.0.x release cycle, a commit in Tail input plugin changed the default behavior on how the Tag was composed when using the wildcard for expansion generating breaking compatibility with other services. Consider the following configuration example:

[INPUT]
    Name  tail
    Path  /var/log/containers/*.log
    Tag   kube.*

The expected behavior is that Tag will be expanded to:

kube.var.log.containers.apache.log

but the change introduced in 1.0 series switched from absolute path to the base file name only:

kube.apache.log

On Fluent Bit v1.1 release we restored to our default behavior and now the Tag is composed using the absolute path of the monitored file.

Having absolute path in the Tag is relevant for routing and flexible configuration where it also helps to keep compatibility with Fluentd behavior.

This behavior switch in Tail input plugin affects how Filter Kubernetes operates. As you know when the filter is used it needs to perform local metadata lookup that comes from the file names when using Tail as a source. Now with the new Kube_Tag_Prefix option you can specify what's the prefix used in Tail input plugin, for the configuration example above the new configuration will look as follows:

[INPUT]
    Name  tail
    Path  /var/log/containers/*.log
    Tag   kube.*

[FILTER]
    Name             kubernetes
    Match            *
    Kube_Tag_Prefix  kube.var.log.containers.

So the proper for Kube_Tag_Prefix value must be composed by Tag prefix set in Tail input plugin plus the converted monitored directory replacing slashes with dots.

Install on Amazon Linux 2

Fluent Bit is distributed as td-agent-bit package and is available for the latest Amazon Linux 2. The following architectures are supported

• x86_64

• aarch64 / arm64v8

Configure Yum

We provide td-agent-bit through a Yum repository. In order to add the repository reference to your system, please add a new file called td-agent-bit.repo in /etc/yum.repos.d/ with the following content:

[td-agent-bit]
name = TD Agent Bit
baseurl = https://packages.fluentbit.io/amazonlinux/2/$basearch/
gpgcheck=1
gpgkey=https://packages.fluentbit.io/fluentbit.key
enabled=1

note: we encourage you always enable the gpgcheck for security reasons. All our packages are signed.

The GPG Key fingerprint is F209 D876 2A60 CD49 E680 633B 4FF8 368B 6EA0 722A

Install

Once your repository is configured, run the following command to install it:

$ yum install td-agent-bit

Now the following step is to instruct systemd to enable the service:

$ sudo service td-agent-bit start

If you do a status check, you should see a similar output like this:

$ service td-agent-bit status
Redirecting to /bin/systemctl status  td-agent-bit.service
● td-agent-bit.service - TD Agent Bit
   Loaded: loaded (/usr/lib/systemd/system/td-agent-bit.service; disabled; vendor preset: disabled)
   Active: active (running) since Thu 2016-07-07 02:08:01 BST; 9s ago
 Main PID: 3820 (td-agent-bit)
   CGroup: /system.slice/td-agent-bit.service
           └─3820 /opt/td-agent-bit/bin/td-agent-bit -c etc/td-agent-bit/td-agent-bit.conf
...

The default configuration of td-agent-bit is collecting metrics of CPU usage and sending the records to the standard output, you can see the outgoing data in your /var/log/messages file.

The following operating systems and architectures are supported in Fluent Bit.

From an architecture support perspective, Fluent Bit is fully functional on x86_64, Arm64v8 and Arm32v7 based processors.

Fluent Bit can work also on OSX and *BSD systems, but not all plugins will be available on all platforms. Official support will be expanding based on community demand.

In production environments we want to have full control of the data we are collecting, filtering is an important feature that allows us to alter the data before delivering it to some destination.

Filtering is implemented through plugins, so each filter available could be used to match, exclude or enrich your logs with some specific metadata.

We support many filters, A common use case for filtering is Kubernetes deployments. Every Pod log needs to get the proper metadata associated

Very similar to the input plugins, Filters run in an instance context, which has its own independent configuration. Configuration keys are often called properties.

​Fluent Bit is an open source and multi-platform log processor tool which aims to be a generic Swiss knife for logs processing and distribution.

Nowadays the number of sources of information in our environments is ever increasing. Handling data collection at scale is complex, and collecting and aggregating diverse data requires a specialized tool that can deal with:

• Different sources of information

• Different data formats

• Data Reliability

• Security

• Flexible Routing

• Multiple destinations

Fluent Bit has been designed with performance and low resources consumption in mind.

Fluent Bit uses very low CPU and Memory consumption, it's compatible with most of x86, x86_64, arm32v7 and arm64v8 based platforms. In order to build it you need the following components in your system for the build process:

• Compiler: GCC or clang

• CMake

• Flex & Bison: only if you enable the Stream Processor or Record Accessor feature (both enabled by default)

In the core there are not other dependencies, For certain features that depends on third party components like output plugins with special backend libraries (e.g: kafka), those are included in the main source code repository.

The output interface allows us to define destinations for the data. Common destinations are remote services, local file system or standard interface with others. Outputs are implemented as plugins and there are many available.

When an output plugin is loaded, an internal instance is created. Every instance has its own independent configuration. Configuration keys are often called properties.

Every output plugin has its own documentation section specifying how it can be used and what properties are available.

For more details, please refer to the Output Plugins section.

Fluent Bit is a Fast and Lightweight Log Processor, Stream Processor and Forwarder for Linux, OSX, Windows and BSD family operating systems. It has been made with a strong focus on performance to allow the collection of events from different sources without complexity.

Features

• High Performance

• Data Parsing

  • Convert your unstructured messages using our parsers: JSON, Regex, LTSV and Logfmt

• Reliability and Data Integrity

  • Backpressure Handling

  • Data Buffering in memory and file system

• Networking

  • Security: built-in TLS/SSL support

  • Asynchronous I/O

• Pluggable Architecture and Extensibility: Inputs, Filters and Outputs

  • More than 50 built-in plugins available

  • Extensibility

    • Write any input, filter or output plugin in C language

    • Bonus: write Filters in Lua or Output plugins in Golang

• Monitoring: expose internal metrics over HTTP in JSON and Prometheus format

• Stream Processing: Perform data selection and transformation using simple SQL queries

  • Create new streams of data using query results

  • Aggregation Windows

  • Data analysis and prediction: Timeseries forecasting

• Portable: runs on Linux, MacOS, Windows and BSD systems

Fluent Bit, Fluentd and CNCF

Fluent Bit is a sub-component of the Fluentd project ecosystem, it's licensed under the terms of the Apache License v2.0. This project was created by Treasure Data and is its current primary sponsor.

Nowadays Fluent Bit get contributions from several companies and individuals and same as Fluentd, it's hosted as a CNCF subproject.

Dealing with raw strings or unstructured messages is a constant pain; having a structure is highly desired. Ideally we want to set a structure to the incoming data by the Input Plugins as soon as they are collected:

The Parser allows you to convert from unstructured to structured data. As a demonstrative 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

The above log line is a raw string without format, ideally we would like to give it a structure that can be processed later easily. If the proper configuration 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 please refer to the Parsers section.

Fluent Bit provides different Input Plugins to gather information from different sources, some of them just collect data from log files while others can gather metrics information from the operating system. There are many plugins for different needs.

When an input plugin is loaded, an internal instance is created. Every instance has its own and independent configuration. Configuration keys are often called properties.

Every input plugin has its own documentation section where it's specified how it can be used and what properties are available.

For more details, please refer to the Input Plugins section.

Install on Redhat / CentOS

Fluent Bit is distributed as td-agent-bit package and is available for the latest stable CentOS system. The following architectures are supported

• x86_64

• aarch64 / arm64v8

Configure Yum

We provide td-agent-bit through a Yum repository. In order to add the repository reference to your system, please add a new file called td-agent-bit.repo in /etc/yum.repos.d/ with the following content:

note: we encourage you always enable the gpgcheck for security reasons. All our packages are signed.

The GPG Key fingerprint is F209 D876 2A60 CD49 E680 633B 4FF8 368B 6EA0 722A

Install

Once your repository is configured, run the following command to install it:

Now the following step is to instruct Systemd to enable the service:

If you do a status check, you should see a similar output like this:

The default configuration of td-agent-bit is collecting metrics of CPU usage and sending the records to the standard output, you can see the outgoing data in your /var/log/messages file.

Fluent Bit source code provides Bitbake recipes to configure, build and package the software for a Yocto based image. Note that specific steps of usage of these recipes in your Yocto environment (Poky) is out of the scope of this documentation.

We distribute two main recipes, one for testing/dev purposes and other with the latest stable release.

It's strongly recommended to always use the stable release of Fluent Bit recipe and not the one from GIT master for production deployments.

Fluent Bit and other architectures

Fluent Bit >= v1.1.x fully supports x86_64, x86, arm32v7 and arm64v8.

Routing is a core feature that allows to route your data through Filters and finally to one or multiple destinations. The router relies on the concept of Tags and Matching rules

There are two important concepts in Routing:

• Tag

• Match

When the data is generated by the input plugins, it comes with a Tag (most of the time the Tag is configured manually), the Tag is a human-readable indicator that helps to identify the data source.

In order to define where the data should be routed, a Match rule must be specified in the output configuration.

Consider the following configuration example that aims to deliver CPU metrics to an Elasticsearch database and Memory metrics to the standard output interface:

[INPUT]
    Name cpu
    Tag  my_cpu

[INPUT]
    Name mem
    Tag  my_mem

[OUTPUT]
    Name   es
    Match  my_cpu

[OUTPUT]
    Name   stdout
    Match  my_mem

Note: the above is a simple example demonstrating how Routing is configured.

Routing works automatically reading the Input Tags and the Output Match rules. If some data has a Tag that doesn't match upon routing time, the data is deleted.

Routing with Wildcard

Routing is flexible enough to support wildcard in the Match pattern. The below example defines a common destination for both sources of data:

[INPUT]
    Name cpu
    Tag  my_cpu

[INPUT]
    Name mem
    Tag  my_mem

[OUTPUT]
    Name   stdout
    Match  my_*

The match rule is set to my_* which means it will match any Tag that starts with my_.

Fluent Bit is distributed as td-agent-bit package and is available for the latest stable Ubuntu system: Focal Fossa.

Server GPG key

The first step is to add our server GPG key to your keyring, on that way you can get our signed packages:

$ wget -qO - https://packages.fluentbit.io/fluentbit.key | sudo apt-key add -

Update your sources lists

On Ubuntu, you need to add our APT server entry to your sources lists, please add the following content at bottom of your /etc/apt/sources.list file:

Ubuntu 20.04 LTS (Focal Fossa)

deb https://packages.fluentbit.io/ubuntu/focal focal main

Ubuntu 18.04 LTS (Bionic Beaver)

deb https://packages.fluentbit.io/ubuntu/bionic bionic main

Ubuntu 16.04 LTS (Xenial Xerus)

deb https://packages.fluentbit.io/ubuntu/xenial xenial main

Update your repositories database

Now let your system update the apt database:

$ sudo apt-get update

Install TD-Agent Bit

Using the following apt-get command you are able now to install the latest td-agent-bit:

$ sudo apt-get install td-agent-bit

Now the following step is to instruct systemd to enable the service:

$ sudo service td-agent-bit start

If you do a status check, you should see a similar output like this:

sudo service td-agent-bit status
● td-agent-bit.service - TD Agent Bit
   Loaded: loaded (/lib/systemd/system/td-agent-bit.service; disabled; vendor preset: enabled)
   Active: active (running) since mié 2016-07-06 16:58:25 CST; 2h 45min ago
 Main PID: 6739 (td-agent-bit)
    Tasks: 1
   Memory: 656.0K
      CPU: 1.393s
   CGroup: /system.slice/td-agent-bit.service
           └─6739 /opt/td-agent-bit/bin/td-agent-bit -c /etc/td-agent-bit/td-agent-bit.conf
...

The default configuration of td-agent-bit is collecting metrics of CPU usage and sending the records to the standard output, you can see the outgoing data in your /var/log/syslog file.

Stable

For production systems, we strongly suggest that you always get the latest stable release from our web site, you can get the official tarballs (.tar.gz) from the following link:

https://fluentbit.io/download/

Development

For people who aims to contribute to the project testing or extending the code base, can get the development version from our GIT repository:

$ git clone https://github.com/fluent/fluent-bit

Note that our master branch is where the development of Fluent Bit happens. Since it's a development version, expect issues when compiling or at run time.

We encourage everybody to help us testing every development version, at the end this is what will become stable.

in normal operation mode allows to be configurable through or using specific arguments in the command line, while this is the ideal deployment case, there are scenarios where a more restricted configuration is required: static configuration mode.

Static configuration mode aims to include a built-in configuration in the final binary of Fluent Bit, disabling the usage of external files or flags at runtime.

Getting Started

Requirements

The following steps assumes you are familiar with configuring Fluent Bit using text files and you have experience building it from scratch as described in the section.

Configuration Directory

In your file system prepare a specific directory that will be used as an entry point for the build system to lookup and parse the configuration files. It is mandatory that this directory contain as a minimum one configuration file called fluent-bit.conf containing the required , and sections. As an example create a new fluent-bit.conf file with the following content:

the configuration provided above will calculate CPU metrics from the running system and print them to the standard output interface.

Build with Custom Configuration

Inside Fluent Bit source code, get into the build/ directory and run CMake appending the FLB_STATIC_CONF option pointing the configuration directory recently created, e.g:

then build it:

At this point the fluent-bit binary generated is ready to run without necessity of further configuration:

Fluent Bit is distributed as td-agent-bit package and is available for the latest (and old) stable Debian systems: Buster, Stretch and Jessie.

Server GPG key

The first step is to add our server GPG key to your keyring, on that way you can get our signed packages:

Update your sources lists

On Debian, you need to add our APT server entry to your sources lists, please add the following content at bottom of your /etc/apt/sources.list file:

Debian 10 (Buster)

Debian 9 (Stretch)

Debian 8 (Jessie)

Update your repositories database

Now let your system update the apt database:

Install TD Agent Bit

Using the following apt-get command you are able now to install the latest td-agent-bit:

Now the following step is to instruct systemd to enable the service:

If you do a status check, you should see a similar output like this:

The default configuration of td-agent-bit is collecting metrics of CPU usage and sending the records to the standard output, you can see the outgoing data in your /var/log/syslog file.

Fluent Bit is distributed as td-agent-bit package and is available for the Raspberry, specifically for Raspbian distribution, the following versions are supported:

• Raspbian Buster (10)

• Raspbian Stretch (9)

• Raspbian Jessie (8)

Server GPG key

The first step is to add our server GPG key to your keyring, on that way you can get our signed packages:

$ wget -qO - https://packages.fluentbit.io/fluentbit.key | sudo apt-key add -

Update your sources lists

On Debian and derivated systems such as Raspbian, you need to add our APT server entry to your sources lists, please add the following content at bottom of your /etc/apt/sources.list file:

Raspbian 10 (Buster)

deb https://packages.fluentbit.io/raspbian/buster buster main

Raspbian 9 (Stretch)

deb https://packages.fluentbit.io/raspbian/stretch stretch main

Raspbian 8 (Jessie)

deb https://packages.fluentbit.io/raspbian/jessie jessie main

Update your repositories database

Now let your system update the apt database:

$ sudo apt-get update

Install TD-Agent Bit

Using the following apt-get command you are able now to install the latest td-agent-bit:

$ sudo apt-get install td-agent-bit

Now the following step is to instruct systemd to enable the service:

$ sudo service td-agent-bit start

If you do a status check, you should see a similar output like this:

sudo service td-agent-bit status
● td-agent-bit.service - TD Agent Bit
   Loaded: loaded (/lib/systemd/system/td-agent-bit.service; disabled; vendor preset: enabled)
   Active: active (running) since mié 2016-07-06 16:58:25 CST; 2h 45min ago
 Main PID: 6739 (td-agent-bit)
    Tasks: 1
   Memory: 656.0K
      CPU: 1.393s
   CGroup: /system.slice/td-agent-bit.service
           └─6739 /opt/td-agent-bit/bin/td-agent-bit -c /etc/td-agent-bit/td-agent-bit.conf
...

The default configuration of td-agent-bit is collecting metrics of CPU usage and sending the records to the standard output, you can see the outgoing data in your /var/log/syslog file.

Fluent Bit container images are available on Docker Hub ready for production usage. Current available images can be deployed in multiple architectures.

Tags and Versions

The following table describe the tags are available on Docker Hub fluent/fluent-bit repository:

It's strongly suggested that you always use the latest image of Fluent Bit.

Multi Architecture Images

Our x86_64 stable image is based in Distroless focusing on security containing just the Fluent Bit binary and minimal system libraries and basic configuration. Optionally, we provide debug images for x86_64 which contains Busybox that can be used to troubleshoot or testing purposes.

In addition, the main manifest provides images for arm64v8 and arm32v7 architectures. From a deployment perspective there is no need to specify an architecture, the container client tool that pulls the image gets the proper layer for the running architecture.

For every architecture we build the layers using the following base images:

Getting Started

Download the last stable image from 1.4 series:

$ docker pull fluent/fluent-bit:1.4

Once the image is in place, now run the following (useless) test which makes Fluent Bit measure CPU usage by the container:

$ docker run -ti fluent/fluent-bit:1.4 /fluent-bit/bin/fluent-bit -i cpu -o stdout -f 1

That command will let Fluent Bit measure CPU usage every second and flush the results to the standard output, e.g:

Fluent-Bit v1.4.x
Copyright (C) Treasure Data

[2019/10/01 12:29:02] [ info] [engine] started
[0] cpu.0: [1504290543.000487750, {"cpu_p"=>0.750000, "user_p"=>0.250000, "system_p"=>0.500000, "cpu0.p_cpu"=>0.000000, "cpu0.p_user"=>0.000000, "cpu0.p_system"=>0.000000, "cpu1.p_cpu"=>1.000000, "cpu1.p_user"=>0.000000, "cpu1.p_system"=>1.000000, "cpu2.p_cpu"=>1.000000, "cpu2.p_user"=>1.000000, "cpu2.p_system"=>0.000000, "cpu3.p_cpu"=>0.000000, "cpu3.p_user"=>0.000000, "cpu3.p_system"=>0.000000}]

F.A.Q

Why there is no Fluent Bit Docker image based on Alpine Linux ?

Alpine Linux uses Musl C library instead of Glibc. Musl is not fully compatible with Glibc which generated many issues in the following areas when used with Fluent Bit:

• Memory Allocator: to run Fluent Bit properly in high-load environments, we use Jemalloc as a default memory allocator which reduce fragmentation and provides better performance for our needs. Jemalloc cannot run smoothly with Musl and requires extra work.

• Alpine Linux Musl functions bootstrap have a compatibility issue when loading Golang shared libraries, this generate problems when trying to load Golang output plugins in Fluent Bit.

• Alpine Linux Musl Time format parser does not support Glibc extensions

• Maintainers preference in terms of base image due to security and maintenance reasons are Distroless and Debian.

Where 'latest' Tag points to ?

Our Docker containers images are deployed thousands of times per day, we take security and stability very seriously.

The latest tag most of the time points to the latest stable image. When we release a major update to Fluent Bit like for example from v1.3.x to v1.4.0, we don't move latest tag until 2 weeks after the release. That give us extra time to verify with our community that everything works as expected.

AWS maintains a distribution of Fluent Bit combining the latest official release with a set of Go Plugins for sending logs to AWS services. AWS and Fluent Bit are working together to rewrite their plugins for inclusion in the official Fluent Bit distribution.

Plugins

Currently, the image contains Go Plugins for:

Versions and Regional Repositories

AWS vends their container image via , and a set of highly available regional Amazon ECR repositories. For more information, see the .

The AWS for Fluent Bit image uses a custom versioning scheme because it contains multiple projects. To see what each release contains, check out the .

SSM Public Parameters

AWS vends SSM Public Parameters with the regional repository link for each image. These parameters can be queried by any AWS account.

To see a list of available version tags in a given region, run the following command:

To see the ECR repository URI for a given image tag in a given region, run the following:

You can use these SSM public parameters as parameters in your CloudFormation templates:

is a lightweight and extensible Log Processor that comes with full support for Kubernetes:

• Process Kubernetes containers logs from the file system or Systemd/Journald.

• Enrich logs with Kubernetes Metadata.

• Centralize your logs in third party storage services like Elasticsearch, InfluxDB, HTTP, etc.

Concepts

Before getting started it is important to understand how Fluent Bit will be deployed. Kubernetes manages a cluster of nodes, so our log agent tool will need to run on every node to collect logs from every POD, hence Fluent Bit is deployed as a DaemonSet (a POD that runs on every node of the cluster).

When Fluent Bit runs, it will read, parse and filter the logs of every POD and will enrich each entry with the following information (metadata):

• Pod Name

• Pod ID

• Container Name

• Container ID

• Labels

• Annotations

To obtain these information, a built-in filter plugin called kubernetes talks to the Kubernetes API Server to retrieve relevant information such as the pod_id, labels and annotations, other fields such as pod_name, container_id and container_name are retrieved locally from the log file names. All of this is handled automatically, no intervention is required from a configuration aspect.

Installation

The next step is to create a ConfigMap that will be used by our Fluent Bit DaemonSet:

Note for Kubernetes < v1.16

For Kubernetes versions olden than v1.16, the DaemonSet resource is not available on apps/v1 , the resource is available on apiVersion: extensions/v1beta1 . Our current Daemonset Yaml files uses the new apiVersion.

If you are using and older Kubernetes, grab manually a copy of your Daemonset Yaml file and replace the value of apiVersion from:

to

You can read more about this deprecation on Kubernetes v1.14 Changelog here:

Fluent Bit to Elasticsearch

Fluent Bit DaemonSet ready to be used with Elasticsearch on a normal Kubernetes Cluster:

Fluent Bit to Elasticsearch on Minikube

If you are using Minikube for testing purposes, use the following alternative DaemonSet manifest:

Details

The default configuration of Fluent Bit makes sure of the following:

• Consume all containers logs from the running Node.

• The Kubernetes filter will enrich the logs with Kubernetes metadata, specifically labels and annotations. The filter only goes to the API Server when it cannot find the cached info, otherwise it uses the cache.

• There is an option called Retry_Limit set to False, that means if Fluent Bit cannot flush the records to Elasticsearch it will re-try indefinitely until it succeed.

The end-goal of is to collect, parse, filter and ship logs to a central place. In this workflow there are many phases and one of the critical pieces is the ability to do buffering : a mechanism to place processed data into a temporal location until is ready to be shipped.

By default when Fluent Bit process data, it uses Memory as a primary and temporal place to store the record logs, but there are certain scenarios where would be ideal to have a persistent buffering mechanism based in the filesystem to provide aggregation and data safety capabilities.

Starting with Fluent Bit v1.0, we introduced a new storage layer that can either work in memory or in the file system. Input plugins can be configured to use one or the other upon demand at start time.

Configuration

The storage layer configuration takes place in two areas:

• Service Section

• Input Section

The known Service section configure a global environment for the storage layer, and then in the Input sections defines which mechanism to use.

Service Section Configuration

The Service section refers to the section defined in the main :

a Service section will look like this:

that configuration configure an optional buffering mechanism where it root for data is /var/log/flb-storage/, it will use normal synchronization mode, without checksum and up to a maximum of 5MB of memory when processing backlog data.

Input Section Configuration

Optionally, any Input plugin can configure their storage preference, the following table describe the options available:

The following example configure a service that offers filesystem buffering capabilities and two Input plugins being the first based in memory and the second with the filesystem:

Fluent Bit might optionally use a configuration file to define how the service will behave, and before proceeding we need to understand how the configuration schema works.

The schema is defined by three concepts:

• Sections

• Entries: Key/Value

• Indented Configuration Mode

A simple example of a configuration file is as follows:

[SERVICE]
    # This is a commented line
    Daemon    off
    log_level debug

Sections

A section is defined by a name or title inside brackets. Looking at the example above, a Service section has been set using [SERVICE] definition. Section rules:

• All section content must be indented (4 spaces ideally).

• Multiple sections can exist on the same file.

• A section is expected to have comments and entries, it cannot be empty.

• Any commented line under a section, must be indented too.

Entries: Key/Value

A section may contain Entries, an entry is defined by a line of text that contains a Key and a Value, using the above example, the [SERVICE] section contains two entries, one is the key Daemon with value off and the other is the key Log_Level with the value debug. Entries rules:

• An entry is defined by a key and a value.

• A key must be indented.

• A key must contain a value which ends in the breakline.

• Multiple keys with the same name can exist.

Also commented lines are set prefixing the # character, those lines are not processed but they must be indented too.

Indented Configuration Mode

Fluent Bit configuration files are based in a strict Indented Mode, that means that each configuration file must follow the same pattern of alignment from left to right when writing text. By default an indentation level of four spaces from left to right is suggested. Example:

[FIRST_SECTION]
    # This is a commented line
    Key1  some value
    Key2  another value
    # more comments

[SECOND_SECTION]
    KeyN  3.14

As you can see there are two sections with multiple entries and comments, note also that empty lines are allowed and they do not need to be indented.

Fluent Bit uses CMake as it build system. The suggested procedure to prepare the build system consists on the following steps:

Prepare environment

In the following steps you can find exact commands to build and install the project with the default options. If you already know how CMake works you can skip this part and look at the build options available.

Change to the build/ directory inside the Fluent Bit sources:

$ cd build/

Let CMake configure the project specifying where the root path is located:

$ cmake ../
-- The C compiler identification is GNU 4.9.2
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- The CXX compiler identification is GNU 4.9.2
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
...
-- Could NOT find Doxygen (missing:  DOXYGEN_EXECUTABLE)
-- Looking for accept4
-- Looking for accept4 - not found
-- Configuring done
-- Generating done
-- Build files have been written to: /home/edsiper/coding/fluent-bit/build

Now you are ready to start the compilation process through the simple make command:

$ make
Scanning dependencies of target msgpack
[  2%] Building C object lib/msgpack-1.1.0/CMakeFiles/msgpack.dir/src/unpack.c.o
[  4%] Building C object lib/msgpack-1.1.0/CMakeFiles/msgpack.dir/src/objectc.c.o
[  7%] Building C object lib/msgpack-1.1.0/CMakeFiles/msgpack.dir/src/version.c.o
...
[ 19%] Building C object lib/monkey/mk_core/CMakeFiles/mk_core.dir/mk_file.c.o
[ 21%] Building C object lib/monkey/mk_core/CMakeFiles/mk_core.dir/mk_rconf.c.o
[ 23%] Building C object lib/monkey/mk_core/CMakeFiles/mk_core.dir/mk_string.c.o
...
Scanning dependencies of target fluent-bit-static
[ 66%] Building C object src/CMakeFiles/fluent-bit-static.dir/flb_pack.c.o
[ 69%] Building C object src/CMakeFiles/fluent-bit-static.dir/flb_input.c.o
[ 71%] Building C object src/CMakeFiles/fluent-bit-static.dir/flb_output.c.o
...
Linking C executable ../bin/fluent-bit
[100%] Built target fluent-bit-bin

to continue installing the binary on the system just do:

$ make install

it's likely you may need root privileges so you can try to prefixing the command with sudo.

Build Options

Fluent Bit provides certain options to CMake that can be enabled or disabled when configuring, please refer to the following tables under the General Options, Development Options, Input Plugins and _Output Plugins sections.

General Options

Development Options

Input Plugins

The input plugins provides certain features to gather information from a specific source type which can be a network interface, some built-in metric or through a specific input device, the following input plugins are available:

Filter Plugins

The filter plugins allows to modify, enrich or drop records. The following table describes the filters available on this version:

Output Plugins

The output plugins gives the capacity to flush the information to some external interface, service or terminal, the following table describes the output plugins available as of this version:

Fluent Bit is distributed as td-agent-bit package for Windows. Fluent Bit has two flavours of Windows installers: a ZIP archive (for quick testing) and an EXE installer (for system installation).

Installation Packages

The latest stable version is 1.4.6.

To check the integrity, use Get-FileHash commandlet on PowerShell.

PS> Get-FileHash td-agent-bit-1.4.6-win32.exe

Installing from ZIP archive

Download a ZIP archive from the download page. There are installers for 32-bit and 64-bit environments, so choose one suitable for your environment.

Then you need to expand the ZIP archive. You can do this by clicking "Extract All" on Explorer, or if you're using PowerShell, you can use Expand-Archive commandlet.

PS> Expand-Archive td-agent-bit-1.4.6-win64.zip

The ZIP package contains the following set of files.

td-agent-bit
├── bin
│   ├── fluent-bit.dll
│   └── fluent-bit.exe
├── conf
│   ├── fluent-bit.conf
│   ├── parsers.conf
│   └── plugins.conf
└── include
    │   ├── flb_api.h
    │   ├── ...
    │   └── flb_worker.h
    └── fluent-bit.h

Now, launch cmd.exe or PowerShell on your machine, and execute fluent-bit.exe as follows.

PS> .\bin\fluent-bit.exe -i dummy -o stdout

If you see the following output, it's working fine!

PS> .\bin\fluent-bit.exe  -i dummy -o stdout
Fluent Bit v1.4.x
* Copyright (C) 2019-2020 The Fluent Bit Authors
* Copyright (C) 2015-2018 Treasure Data
* Fluent Bit is a CNCF sub-project under the umbrella of Fluentd
* https://fluentbit.io

[2019/06/28 10:13:04] [ info] [storage] initializing...
[2019/06/28 10:13:04] [ info] [storage] in-memory
[2019/06/28 10:13:04] [ info] [storage] normal synchronization mode, checksum disabled, max_chunks_up=128
[2019/06/28 10:13:04] [ info] [engine] started (pid=10324)
[2019/06/28 10:13:04] [ info] [sp] stream processor started
[0] dummy.0: [1561684385.443823800, {"message"=>"dummy"}]
[1] dummy.0: [1561684386.428399000, {"message"=>"dummy"}]
[2] dummy.0: [1561684387.443641900, {"message"=>"dummy"}]
[3] dummy.0: [1561684388.441405800, {"message"=>"dummy"}]

To halt the process, press CTRL-C in the terminal.

Installing from EXE installer

Download an EXE installer from the download page. It has both 32-bit and 64-bit builds. Choose one which is suitable for you.

Then, double-click the EXE installer you've downloaded. Installation wizard will automatically start.

Click Next and proceed. By default, Fluent Bit is installed into C:\Program Files\td-agent-bit\, so you should be able to launch fluent-bit as follow after installation.

PS> C:\Program Files\td-agent-bit\bin\fluent-bit.exe -i dummy -o stdout

One of the ways to configure Fluent Bit is using a main configuration file. Fluent Bit allows to use one configuration file which works at a global scope and uses the Format and Schema defined previously.

The main configuration file supports four types of sections:

• Service

• Input

• Filter

• Output

In addition, it's also possible to split the main configuration file in multiple files using the feature to include external files:

• Include File

Service

The Service section defines global properties of the service, the keys available as of this version are described in the following table:

The following is an example of a SERVICE section:

[SERVICE]
    Flush           5
    Daemon          off
    Log_Level       debug

Input

An INPUT section defines a source (related to an input plugin), here we will describe the base configuration for each INPUT section. Note that each input plugin may add it own configuration keys:

The Name is mandatory and it let Fluent Bit know which input plugin should be loaded. The Tag is mandatory for all plugins except for the input forward plugin (as it provides dynamic tags).

Example

The following is an example of an INPUT section:

[INPUT]
    Name cpu
    Tag  my_cpu

Filter

A FILTER section defines a filter (related to an filter plugin), here we will describe the base configuration for each FILTER section. Note that each filter plugin may add it own configuration keys:

The Name is mandatory and it let Fluent Bit know which filter plugin should be loaded. The Match or Match_Regex is mandatory for all plugins. If both are specified, Match_Regex takes precedence.

Example

The following is an example of an FILTER section:

[FILTER]
    Name  stdout
    Match *

Output

The OUTPUT section specify a destination that certain records should follow after a Tag match. The configuration support the following keys:

Example

The following is an example of an OUTPUT section:

[OUTPUT]
    Name  stdout
    Match my*cpu

Example: collecting CPU metrics

The following configuration file example demonstrates how to collect CPU metrics and flush the results every five seconds to the standard output:

[SERVICE]
    Flush     5
    Daemon    off
    Log_Level debug

[INPUT]
    Name  cpu
    Tag   my_cpu

[OUTPUT]
    Name  stdout
    Match my*cpu

Include File

To avoid complicated long configuration files is better to split specific parts in different files and call them (include) from one main file.

Starting from Fluent Bit 0.12 the new configuration command @INCLUDE has been added and can be used in the following way:

@INCLUDE somefile.conf

The configuration reader will try to open the path somefile.conf, if not found, it will assume it's a relative path based on the path of the base configuration file, e.g:

• Main configuration file path: /tmp/main.conf

• Included file: somefile.conf

• Fluent Bit will try to open somefile.conf, if it fails it will try /tmp/somefile.conf.

Once the file is found, its contents will replace the @INCLUDE somefile.conf line. This is a simple textual inclusion. You must still follow the Format and Schema defined previously. For example, you cannot define multiple [SERVICE] sections.

The @INCLUDE command only works at top-left level of the configuration line, it cannot be used inside sections.

Wildcard character (*) is supported to include multiple files, e.g:

@INCLUDE input_*.conf

Learn how to .

In certain scenarios would be ideal to estimate how much memory Fluent Bit could be using, this is very useful for containerized environments where memory limits are a must.

In order to estimate we will assume that the input plugins have set the Mem_Buf_Limit option (you can learn more about it in the section).

Estimating

Input plugins append data independently, so in order to do an estimation a limit should be imposed through the Mem_Buf_Limit option. If the limit was set to 10MB we need to estimate that in the worse case, the output plugin likely could use 20MB.

Fluent Bit has an internal binary representation for the data being processed, but when this data reach an output plugin, this one will likely create their own representation in a new memory buffer for processing. The best example are the and output plugins, both needs to convert the binary representation to their respective-custom JSON formats before to talk to their backend servers.

So, if we impose a limit of 10MB for the input plugins and considering the worse case scenario of the output plugin consuming 20MB extra, as a minimum we need (30MB x 1.2) = 36MB.

Glibc and Memory Fragmentation

Is well known that in intensive environments where memory allocations happens in the order of magnitude, the default memory allocator provided by Glibc could lead to a high fragmentation, reporting a high memory usage by the service.

It's strongly suggested that in any production environment, Fluent Bit should be built with enabled (e.g. -DFLB_JEMALLOC=On). Jemalloc is an alternative memory allocator that can reduce fragmentation (among others things) resulting in better performance.

You can check if Fluent Bit has been built with Jemalloc using the following command:

The output should looks like:

If the FLB_HAVE_JEMALLOC option is listed in Build Flags, everything will be fine.

Fluent Bit supports the usage of environment variables in any value associated to a key when using a configuration file.

The variables are case sensitive and can be used in the following format:

${MY_VARIABLE}

When Fluent Bit starts, the configuration reader will detect any request for ${MY_VARIABLE} and will try to resolve its value.

Example

Create the following configuration file (fluent-bit.conf):

[SERVICE]
    Flush        1
    Daemon       Off
    Log_Level    info

[INPUT]
    Name cpu
    Tag  cpu.local

[OUTPUT]
    Name  ${MY_OUTPUT}
    Match *

Open a terminal and set the environment variable:

$ export MY_OUTPUT=stdout

The above command set the 'stdout' value to the variable MY_OUTPUT.

Run Fluent Bit with the recently created configuration file:

$ bin/fluent-bit -c fluent-bit.conf
Fluent Bit v1.4.0
* Copyright (C) 2019-2020 The Fluent Bit Authors
* Copyright (C) 2015-2018 Treasure Data
* Fluent Bit is a CNCF sub-project under the umbrella of Fluentd
* https://fluentbit.io

[2020/03/03 12:25:25] [ info] [engine] started
[0] cpu.local: [1491243925, {"cpu_p"=>1.750000, "user_p"=>1.750000, "system_p"=>0.000000, "cpu0.p_cpu"=>3.000000, "cpu0.p_user"=>2.000000, "cpu0.p_system"=>1.000000, "cpu1.p_cpu"=>0.000000, "cpu1.p_user"=>0.000000, "cpu1.p_system"=>0.000000, "cpu2.p_cpu"=>4.000000, "cpu2.p_user"=>4.000000, "cpu2.p_system"=>0.000000, "cpu3.p_cpu"=>1.000000, "cpu3.p_user"=>1.000000, "cpu3.p_system"=>0.000000}]

As you can see the service worked properly as the configuration was valid.

Fluent Bit comes with a built-in HTTP Server that can be used to query internal information and monitor metrics of each running plugin.

The monitoring interface can be easily integrated with Prometheus since we support it native format.

Getting Started

To get started, the first step is to enable the HTTP Server from the configuration file:

[SERVICE]
    HTTP_Server  On
    HTTP_Listen  0.0.0.0
    HTTP_PORT    2020

[INPUT]
    Name cpu

[OUTPUT]
    Name  stdout
    Match *

the above configuration snippet will instruct Fluent Bit to start it HTTP Server on TCP Port 2020 and listening on all network interfaces:

$ bin/fluent-bit -c fluent-bit.conf
Fluent Bit v1.4.0
* Copyright (C) 2019-2020 The Fluent Bit Authors
* Copyright (C) 2015-2018 Treasure Data
* Fluent Bit is a CNCF sub-project under the umbrella of Fluentd
* https://fluentbit.io

[2020/03/10 19:08:24] [ info] [engine] started
[2020/03/10 19:08:24] [ info] [http_server] listen iface=0.0.0.0 tcp_port=2020

now with a simple curl command is enough to gather some information:

$ curl -s http://127.0.0.1:2020 | jq
{
  "fluent-bit": {
    "version": "0.13.0",
    "edition": "Community",
    "flags": [
      "FLB_HAVE_TLS",
      "FLB_HAVE_METRICS",
      "FLB_HAVE_SQLDB",
      "FLB_HAVE_TRACE",
      "FLB_HAVE_HTTP_SERVER",
      "FLB_HAVE_FLUSH_LIBCO",
      "FLB_HAVE_SYSTEMD",
      "FLB_HAVE_VALGRIND",
      "FLB_HAVE_FORK",
      "FLB_HAVE_PROXY_GO",
      "FLB_HAVE_REGEX",
      "FLB_HAVE_C_TLS",
      "FLB_HAVE_SETJMP",
      "FLB_HAVE_ACCEPT4",
      "FLB_HAVE_INOTIFY"
    ]
  }
}

Note that we are sending the curl command output to the jq program which helps to make the JSON data easy to read from the terminal. Fluent Bit don't aim to do JSON pretty-printing.

REST API Interface

Fluent Bit aims to expose useful interfaces for monitoring, as of Fluent Bit v0.14 the following end points are available:

Uptime Example

Query the service uptime with the following command:

$ curl -s http://127.0.0.1:2020/api/v1/uptime | jq

it should print a similar output like this:

{
  "uptime_sec": 8950000,
  "uptime_hr": "Fluent Bit has been running:  103 days, 14 hours, 6 minutes and 40 seconds"
}

Metrics Examples

Query internal metrics in JSON format with the following command:

$ curl -s http://127.0.0.1:2020/api/v1/metrics | jq

it should print a similar output like this:

{
  "input": {
    "cpu.0": {
      "records": 8,
      "bytes": 2536
    }
  },
  "output": {
    "stdout.0": {
      "proc_records": 5,
      "proc_bytes": 1585,
      "errors": 0,
      "retries": 0,
      "retries_failed": 0
    }
  }
}

Metrics in Prometheus format

Query internal metrics in Prometheus Text 0.0.4 format:

$ curl -s http://127.0.0.1:2020/api/v1/metrics/prometheus

this time the same metrics will be in Prometheus format instead of JSON:

fluentbit_input_records_total{name="cpu.0"} 57 1509150350542
fluentbit_input_bytes_total{name="cpu.0"} 18069 1509150350542
fluentbit_output_proc_records_total{name="stdout.0"} 54 1509150350542
fluentbit_output_proc_bytes_total{name="stdout.0"} 17118 1509150350542
fluentbit_output_errors_total{name="stdout.0"} 0 1509150350542
fluentbit_output_retries_total{name="stdout.0"} 0 1509150350542
fluentbit_output_retries_failed_total{name="stdout.0"} 0 1509150350542

Configuring Aliases

By default configured plugins on runtime get an internal name in the format plugin_name.ID. For monitoring purposes this can be confusing if many plugins of the same type were configured. To make a distinction each configured input or output section can get an alias that will be used as the parent name for the metric.

The following example set an alias to the INPUT section which is using the CPU input plugin:

[SERVICE]
    HTTP_Server  On
    HTTP_Listen  0.0.0.0
    HTTP_PORT    2020

[INPUT]
    Name  cpu
    Alias server1_cpu

[OUTPUT]
    Name  stdout
    Alias raw_output
    Match *

Now when querying the metrics we get the aliases in place instead of the plugin name:

{
  "input": {
    "server1_cpu": {
      "records": 8,
      "bytes": 2536
    }
  },
  "output": {
    "raw_output": {
      "proc_records": 5,
      "proc_bytes": 1585,
      "errors": 0,
      "retries": 0,
      "retries_failed": 0
    }
  }
}

Certain configuration directives in Fluent Bit refer to unit sizes such as when defining the size of a buffer or specific limits, we can find these in plugins like Tail Input, Forward Input or in generic properties like Mem_Buf_Limit.

Starting from Fluent Bit v0.11.10, all unit sizes have been standardized across the core and plugins, the following table describes the options that can be used and what they mean:

In certain environments is common to see that logs or data being ingested is faster than the ability to flush it to some destinations. The common case is reading from big log files and dispatching the logs to a backend over the network which takes some time to respond, this generate backpressure leading to a high memory consumption in the service.

In order to avoid backpressure, Fluent Bit implements a mechanism in the engine that restrict the amount of data than an input plugin can ingest, this is done through the configuration parameter Mem_Buf_Limit.

Mem_Buf_Limit

This option is disabled by default and can be applied to all input plugins. Let's explain it behavior using the following scenario:

• Mem_Buf_Limit is set to 1MB (one megabyte)

• input plugin tries to append 700KB

• engine route the data to an output plugin

• output plugin backend (HTTP Server) is down

• engine scheduler will retry the flush after 10 seconds

• input plugin tries to append 500KB

At this exact point, the engine will allow to append those 500KB of data into the engine: in total we have 1.2MB. The options works in a permissive mode before to reach the limit, but the limit is exceeded the following actions are taken:

• block local buffers for the input plugin (cannot append more data)

• notify the input plugin invoking a pause callback

The engine will protect it self and will not append more data coming from the input plugin in question; Note that is the plugin responsibility to keep their state and take some decisions about what to do on that paused state.

After some seconds if the scheduler was able to flush the initial 700KB of data or it gave up after retrying, that amount memory is released and internally the following actions happens:

• Upon data buffer release (700KB), the internal counters get updated

• Counters now are set at 500KB

• Since 500KB is < 1MB it checks the input plugin state

• If the plugin is paused, it invokes a resume callback

• input plugin can continue appending more data

About pause and resume Callbacks

Each plugin is independent and not all of them implements the pause and resume callbacks. As said, these callbacks are just a notification mechanism for the plugin.

The plugin who implements and keep a good state is the Tail Input plugin. When the pause callback is triggered, it stop their collectors and stop appending data. Upon resume, it re-enable the collectors.

It's common that Fluent Bit output plugins aims to connect to external services to deliver the logs over the network, this is the case of HTTP, Elasticsearch and Forward within others. Being able to connect to one node (host) is normal and enough for more of the use cases, but there are other scenarios where balancing across different nodes is required. The Upstream feature provides such capability.

An Upstream defines a set of nodes that will be targeted by an output plugin, by the nature of the implementation an output plugin must support the Upstream feature. The following plugin(s) have Upstream support:

• Forward

The current balancing mode implemented is round-robin.

Configuration

To define an Upstream it's required to create an specific configuration file that contains an UPSTREAM and one or multiple NODE sections. The following table describe the properties associated to each section. Note that all of them are mandatory:

Nodes and specific plugin configuration

A Node might contain additional configuration keys required by the plugin, on that way we provide enough flexibility for the output plugin, a common use case is Forward output where if TLS is enabled, it requires a shared key (more details in the example below).

Nodes and TLS (Transport Layer Security)

In addition to the properties defined in the table above, the network operations against a defined node can optionally be done through the use of TLS for further encryption and certificates use.

The TLS options available are described in the TLS/SSL section and can be added to the any Node section.

Configuration File Example

The following example defines an Upstream called forward-balancing which aims to be used by Forward output plugin, it register three Nodes:

• node-1: connects to 127.0.0.1:43000

• node-2: connects to 127.0.0.1:44000

• node-3: connects to 127.0.0.1:45000 using TLS without verification. It also defines a specific configuration option required by Forward output called shared_key.

[UPSTREAM]
    name       forward-balancing

[NODE]
    name       node-1
    host       127.0.0.1
    port       43000

[NODE]
    name       node-2
    host       127.0.0.1
    port       44000

[NODE]
    name       node-3
    host       127.0.0.1
    port       45000
    tls        on
    tls.verify off
    shared_key secret

Note that every Upstream definition must exists on it own configuration file in the file system. Adding multiple Upstreams in the same file or different files is not allowed.

Fluent Bit provides integrated support for Transport Layer Security (TLS) and it predecessor Secure Sockets Layer (SSL) respectively. In this section we will refer as TLS only for both implementations.

Each output plugin that requires to perform Network I/O can optionally enable TLS and configure the behavior. The following table describes the properties available:

The listed properties can be enabled in the configuration file, specifically on each output plugin section or directly through the command line.

The following output plugins can take advantage of the TLS feature:

• Azure

• BigQuery

• Datadog

• Elasticsearch

• Forward

• GELF

• HTTP

• InfluxDB

• Kafka REST Proxy

• Slack

• Splunk

• Stackdriver

• TCP & TLS

• Treasure Data

In addition, other plugins implements a sub-set of TLS support, meaning, with restricted configuration:

• Kubernetes Filter

Example: enable TLS on HTTP output

By default HTTP output plugin uses plain TCP, enabling TLS from the command line can be done with: