Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
The output plugins defines where Fluent Bit should flush the information it gather from the input. At the moment the available options are the following:
name
title
description
Azure Log Analytics
Ingest records into Azure Log Analytics
BigQuery
Ingest records into Google BigQuery
Count Records
Simple records counter.
Elasticsearch
flush records to a Elasticsearch server.
File
Flush records to a file.
FlowCounter
Count records.
Forward
Fluentd forward protocol.
HTTP
Flush records to an HTTP end point.
InfluxDB
Flush records to InfluxDB time series database.
Apache Kafka
Flush records to Apache Kafka
Kafka REST Proxy
Flush records to a Kafka REST Proxy server.
Google Stackdriver Logging
Flush records to Google Stackdriver Logging service.
Standard Output
Flush records to the standard output.
Splunk
Flush records to a Splunk Enterprise service
Flush records to the Treasure Data cloud service for analytics.
NATS
flush records to a NATS server.
NULL
throw away events.
The es output plugin, allows to flush your records into a database. The following instructions assumes that you have a fully operational Elasticsearch service running in your environment.
The parameters index and type can be confusing if you are new to Elastic, if you have used a common relational database before, they can be compared to the database and table concepts.
In order to insert records into a Elasticsearch service, you can run the plugin from the command line or through the configuration file:
The es plugin, can read the parameters from the command line in two ways, through the -p argument (property) or setting them directly through the service URI. The URI format is the following:
Using the format specified, you could start Fluent Bit through:
which is similar to do:
In your main configuration file append the following Input & Output sections:
Some input plugins may generate messages where the field names contains dots, since Elasticsearch 2.0 this is not longer allowed, so the current es plugin replaces them with an underscore, e.g:
becomes
Elasticsearch output plugin supports TTL/SSL, for more details about the properties available and general configuration, please refer to the section.
Counter is a very simple plugin that counts how many records it's getting upon flush time. Plugin output is as follows:
You can run the plugin from the command line or through the configuration file:
From the command line you can let Fluent Bit count up a data with the following options:
In your main configuration file append the following Input & Output sections:
Once Fluent Bit is running, you will see the reports in the output interface similar to this:
Key | Description | default |
Host | IP address or hostname of the target Elasticsearch instance | 127.0.0.1 |
Port | TCP port of the target Elasticsearch instance | 9200 |
Path | Elasticsearch accepts new data on HTTP query path "/_bulk". But it is also possible to serve Elasticsearch behind a reverse proxy on a subpath. This option defines such path on the fluent-bit side. It simply adds a path prefix in the indexing HTTP POST URI. | Empty string |
Buffer_Size | 4KB |
Pipeline | Newer versions of Elasticsearch allows to setup filters called pipelines. This option allows to define which pipeline the database should use. For performance reasons is strongly suggested to do parsing and filtering on Fluent Bit side, avoid pipelines. |
HTTP_User | Optional username credential for Elastic X-Pack access |
HTTP_Passwd | Password for user defined in HTTP_User |
Index | Index name | fluentbit |
Type | Type name | flb_type |
Logstash_Format | Enable Logstash format compatibility. This option takes a boolean value: True/False, On/Off | Off |
Logstash_Prefix | When Logstash_Format is enabled, the Index name is composed using a prefix and the date, e.g: If Logstash_Prefix is equals to 'mydata' your index will become 'mydata-YYYY.MM.DD'. The last string appended belongs to the date when the data is being generated. | logstash |
Logstash_DateFormat | %Y.%m.%d |
Time_Key | When Logstash_Format is enabled, each record will get a new timestamp field. The Time_Key property defines the name of that field. | @timestamp |
Time_Key_Format | When Logstash_Format is enabled, this property defines the format of the timestamp. | %Y-%m-%dT%H:%M:%S |
Include_Tag_Key | When enabled, it append the Tag name to the record. | Off |
Tag_Key | When Include_Tag_Key is enabled, this property defines the key name for the tag. | _flb-key |
Generate_ID | When enabled, generate | Off |
Replace_Dots | When enabled, replace field name dots with underscore, required by Elasticsearch 2.0-2.3. | Off |
Trace_Output | When enabled print the elasticsearch API calls to stdout (for diag only) | Off |
Current_Time_Index | Use current time for index generation instead of message record | Off |
Logstash_Prefix_Key | Prefix keys with this string |
BigQuery output plugin is and experimental plugin that allows you to stream records into Google Cloud BigQuery service. The implementation does not support the following, which would be expected in a full production version:
Data deduplication using insertId.
Template tables using templateSuffix.
Fluent Bit streams data into an existing BigQuery table using a service account that you specify. Therefore, before using the BigQuery output plugin, you must create a service account, create a BigQuery dataset and table, authorize the service account to write to the table, and provide the service account credentials to Fluent Bit.
To stream data into BigQuery, the first step is to create a Google Cloud service account for Fluent Bit:
Fluent Bit does not create datasets or tables for your data, so you must create these ahead of time. You must also grant the service account WRITER permission on the dataset:
Within the dataset you will need to create a table for the data to reside in. You can follow the following instructions for creating your table. Pay close attention to the schema. It must match the schema of your output JSON. Unfortunately, since BigQuery does not allow dots in field names, you will need to use a filter to change the fields for many of the standard inputs (e.g, mem or cpu).
Fluent Bit BigQuery output plugin uses a JSON credentials file for authentication credentials. Download the credentials file by following these instructions:
If you are using a Google Cloud Credentials File, the following configuration is enough to get you started:
Azure output plugin allows to ingest your records into Azure Log Analytics service.
To get more details about how to setup the Azure Log Analytics please refer to the following documentation: Azure Log Analytics
In order to insert records into a Azure, you can run the plugin from the command line or through the configuration file:
The azure plugin, can read the parameters from the command line in two ways, through the -p argument (property), e.g:
In your main configuration file append the following Input & Output sections:
FlowCounter is the protocol to count records. The flowcounter output plugin allows to count up records and its size.
The plugin supports the following configuration parameters:
You can run the plugin from the command line or through the configuration file:
From the command line you can let Fluent Bit count up a data with the following options:
In your main configuration file append the following Input & Output sections:
Once Fluent Bit is running, you will see the reports in the output interface similar to this:
The file output plugin allows to write the data received through the input plugin to file.
The plugin supports the following configuration parameters:
Output time, tag and json records. There is no configuration parameters for out_file.
Output the records as JSON (without additional tag and timestamp attributes). There is no configuration parameters for plain format.
Output the records as csv. Csv supports an additional configuration parameter.
Output the records as LTSV. LTSV supports an additional configuration parameter.
You can run the plugin from the command line or through the configuration file:
From the command line you can let Fluent Bit count up a data with the following options:
In your main configuration file append the following Input & Output sections:
Forward is the protocol used by Fluentd to route messages between peers. The forward output plugin allows to provide interoperability between Fluent Bit and Fluentd. There are not configuration steps required besides to specify where Fluentd is located, it can be in the local host or a in a remote machine.
This plugin offers two different transports and modes:
Forward (TCP): It uses a plain TCP connection.
Secure Forward (TLS): when TLS is enabled, the plugin switch to Secure Forward mode.
The following parameters are mandatory for either Forward for Secure Forward modes:
When using Secure Forward mode, the TLS mode requires to be enabled. The following additional configuration parameters are available:
Before proceeding, make sure that Fluentd is installed in your system, if it's not the case please refer to the following Fluentd Installation document and go ahead with that.
Once Fluentd is installed, create the following configuration file example that will allow us to stream data into it:
That configuration file specifies that it will listen for TCP connections on the port 24224 through the forward input type. Then for every message with a fluent_bit TAG, will print the message to the standard output.
In one terminal launch Fluentd specifying the new configuration file created (in_fluent-bit.conf):
Now that Fluentd is ready to receive messages, we need to specify where the forward output plugin will flush the information using the following format:
If the TAG parameter is not set, the plugin will set the tag as fluent_bit. Keep in mind that TAG is important for routing rules inside Fluentd.
Using the CPU input plugin as an example we will flush CPU metrics to Fluentd:
Now on the Fluentd side, you will see the CPU metrics gathered in the last seconds:
So we gathered CPU metrics and flushed them out to Fluentd properly.
DISCLAIMER: the following example do not consider the generation of certificates for a proper usage of production environments.
Secure Forward aims to provide a secure channel of communication with the remote Fluentd service using TLS. Above there is a minimalist configuration for testing purposes.
Paste this content in a file called flb.conf:
Paste this content in a file called fld.conf:
If you're using Fluentd v1, set up it as below:
Start Fluentd:
Start Fluent Bit:
After five seconds, Fluent Bit will write the records to Fluentd. In Fluentd output you will see a message like this:
The http output plugin allows to flush your records into a HTTP endpoint. For now the functionality is pretty basic and it issues a POST request with the data records in (or JSON) format.
HTTP output plugin supports TTL/SSL, for more details about the properties available and general configuration, please refer to the section.
In order to insert records into a HTTP server, you can run the plugin from the command line or through the configuration file:
The http plugin, can read the parameters from the command line in two ways, through the -p argument (property) or setting them directly through the service URI. The URI format is the following:
Using the format specified, you could start Fluent Bit through:
In your main configuration file, append the following Input & Output sections:
By default, the URI becomes tag of the message, the original tag is ignored. To retain the tag, multiple configuration sections have to be made based and flush to different URIs.
Another approach we also support is the sending the original message tag in a configurable header. It's up to the receiver to do what it wants with that header field: parse it and use it as the tag for example.
To configure this behaviour, add this config:
Provided you are using Fluentd as data receiver, you can combine in_http and out_rewrite_tag_filter to make use of this HTTP header.
Notice how we override the tag, which is from URI path, with our custom header
Kafka output plugin allows to ingest your records into an service. This plugin use the official (built-in dependency)
Setting
rdkafka.log.connection.closetofalseandrdkafka.request.required.acksto 1 are examples of recommended settings of librdfkafka properties.
In order to insert records into Apache Kafka, you can run the plugin from the command line or through the configuration file:
The splunk plugin, can read the parameters from the command line in two ways, through the -p argument (property), e.g:
In your main configuration file append the following Input & Output sections:
The influxdb output plugin, allows to flush your records into a time series database. The following instructions assumes that you have a fully operational InfluxDB service running in your system.
InfluxDB output plugin supports TTL/SSL, for more details about the properties available and general configuration, please refer to the section.
In order to start inserting records into an InfluxDB service, you can run the plugin from the command line or through the configuration file:
The influxdb plugin, can read the parameters from the command line in two ways, through the -p argument (property) or setting them directly through the service URI. The URI format is the following:
Using the format specified, you could start Fluent Bit through:
In your main configuration file append the following Input & Output sections:
Basic example of Tag_Keys usage:
With Auto_Tags=On in this example cause error, because every parsed field value type is string. Best usage of this option in metrics like record where one ore more field value is not string typed.
Before to start Fluent Bit, make sure the target database exists on InfluxDB, using the above example, we will insert the data into a fluentbit database.
Log into InfluxDB console:
Create the database:
Check the database exists:
The following command will gather CPU metrics from the system and send the data to InfluxDB database every five seconds:
Note that all records coming from the cpu input plugin, have a tag cpu, this tag is used to generate the measurement in InfluxDB
From InfluxDB console, choose your database:
Now query some specific fields:
The CPU input plugin gather more metrics per CPU core, in the above example we just selected three specific metrics. The following query will give a full result:
Query tagged keys:
And now query method key values:
The null output plugin just throws away events.
The plugin doesn't support configuration parameters.
You can run the plugin from the command line or through the configuration file:
From the command line you can let Fluent Bit throws away events with the following options:
In your main configuration file append the following Input & Output sections:
The kafka-rest output plugin, allows to flush your records into a server. The following instructions assumes that you have a fully operational Kafka REST Proxy and Kafka services running in your environment.
Kafka REST Proxy output plugin supports TTL/SSL, for more details about the properties available and general configuration, please refer to the section.
In order to insert records into a Kafka REST Proxy service, you can run the plugin from the command line or through the configuration file:
The kafka-rest plugin, can read the parameters from the command line in two ways, through the -p argument (property), e.g:
In your main configuration file append the following Input & Output sections:
The nats output plugin, allows to flush your records into a end point. The following instructions assumes that you have a fully operational NATS Server in place.
In order to flush records, the nats plugin requires to know two parameters:
In order to override the default configuration values, the plugin uses the optional Fluent Bit network address format, e.g:
only requires to know that it needs to use the nats output plugin, if no extra information is given, it will use the default values specified in the above table.
As described above, the target service and storage point can be changed, e.g:
For every set of records flushed to a NATS Server, Fluent Bit uses the following JSON format:
Each record is an individual entity represented in a JSON array that contains a UNIX_TIMESTAMP and a JSON map with a set of key/values. A summarized output of the CPU input plugin will looks as this:
Specify the buffer size used to read the response from the Elasticsearch HTTP service. This option is useful for debugging purposes where is required to read full responses, note that response size grows depending of the number of records inserted. To set an unlimited amount of memory set this value to False, otherwise the value must be according to the specification.
Time format (based on ) to generate the second part of the Index name.
Key
Description
default
Customer_ID
Customer ID or WorkspaceID string.
Shared_Key
The primary or the secondary Connected Sources client authentication key.
Log_Type
The name of the event type.
fluentbit
Key
Description
default
google_service_credentials
Absolute path to a Google Cloud credentials JSON file
Value of the environment variable $GOOGLE_SERVICE_CREDENTIALS
project_id
The project id containing the BigQuery dataset to stream into.
The value of the project_id in the credentials file
dataset_id
The dataset id of the BigQuery dataset to write into. This dataset must exist in your project.
table_id
The table id of the BigQuery table to write into. This table must exist in the specified dataset and the schema must match the output.
Key
Description
Default
Unit
The unit of duration. (second/minute/hour/day)
minute
Key
Description
Path
File path to output. If not set, the filename will be tag name.
Format
The format of the file content. See also Format section. Default: out_file.
Key
Description
Delimiter
The character to separate each data. Default: ','
Key
Description
Delimiter
The character to separate each pair. Default: '\t'(TAB)
Label_Delimiter
The character to separate label and the value. Default: ':'
Key
Description
Default
Host
Target host where Fluent-Bit or Fluentd are listening for Forward messages.
127.0.0.1
Port
TCP Port of the target service.
24224
Time_as_Integer
Set timestamps in integer format, it enable compatibility mode for Fluentd v0.12 series.
False
Upstream
If Forward will connect to an Upstream instead of a simple host, this property defines the absolute path for the Upstream configuration file, for more details about this refer to the Upstream Servers documentation section.
Key
Description
Default
Shared_Key
A key string known by the remote Fluentd used for authorization.
Self_Hostname
Default value of the auto-generated certificate common name (CN).
tls
Enable or disable TLS support
Off
tls.verify
Force certificate validation
On
tls.debug
Set TLS debug verbosity level. It accept the following values: 0 (No debug), 1 (Error), 2 (State change), 3 (Informational) and 4 Verbose
1
tls.ca_file
Absolute path to CA certificate file
tls.crt_file
Absolute path to Certificate file.
tls.key_file
Absolute path to private Key file.
tls.key_passwd
Optional password for tls.key_file file.
Key | Description | default |
Host | IP address or hostname of the target InfluxDB service | 127.0.0.1 |
Port | TCP port of the target InfluxDB service | 8086 |
Database | InfluxDB database name where records will be inserted | fluentbit |
Sequence_Tag | The name of the tag whose value is incremented for the consecutive simultaneous events. | _seq |
HTTP_User | Optional username for HTTP Basic Authentication |
HTTP_Passwd | Password for user defined in HTTP_User |
Tag_Keys | Space separated list of keys that needs to be tagged |
Auto_Tags | Automatically tag keys where value is string. This option takes a boolean value: True/False, On/Off. | Off |
Key | Description | default |
Host | IP address or hostname of the target Kafka REST Proxy server | 127.0.0.1 |
Port | TCP port of the target Kafka REST Proxy server | 8082 |
Topic | Set the Kafka topic | fluent-bit |
Partition | Set the partition number (optional) |
Message_Key | Set a message key (optional) |
Time_Key | The Time_Key property defines the name of the field that holds the record timestamp. | @timestamp |
Time_Key_Format | Defines the format of the timestamp. | %Y-%m-%dT%H:%M:%S |
Include_Tag_Key | Append the Tag name to the final record. | Off |
Tag_Key | If Include_Tag_Key is enabled, this property defines the key name for the tag. | _flb-key |
parameter | description | default |
host | IP address or hostname of the NATS Server | 127.0.0.1 |
port | TCP port of the target NATS Server | 4222 |
Key | Description | default |
Host | IP address or hostname of the target HTTP Server | 127.0.0.1 |
HTTP_User | Basic Auth Username |
HTTP_Passwd | Basic Auth Password. Requires HTTP_User to be set |
Port | TCP port of the target HTTP Server | 80 |
Proxy |
URI | Specify an optional HTTP URI for the target web server, e.g: /something | / |
Format | Specify the data format to be used in the HTTP request body, by default it uses msgpack. Other supported formats are json, json_stream and json_lines. | msgpack |
header_tag | Specify an optional HTTP header field for the original message tag. |
Header | Add a HTTP header key/value pair. Multiple headers can be set. |
json_date_key | Specify the name of the date field in output | date |
json_date_format | Specify the format of the date. Supported formats are double, epoch, and iso8601 (eg: 2018-05-30T09:39:52.000681Z) | double |
Key | Description | default |
Format | Specify data format, options available: json, msgpack. | json |
Message_Key | Optional key to store the message |
Timestamp_Key | Set the key to store the record timestamp | @timestamp |
Timestamp_Format | 'iso8601' or 'double' | double |
Brokers | Single of multiple list of Kafka Brokers, e.g: 192.168.1.3:9092, 192.168.1.4:9092. |
Topics | Single entry or list of topics separated by comma (,) that Fluent Bit will use to send messages to Kafka. If only one topic is set, that one will be used for all records. Instead if multiple topics exists, the one set in the record by Topic_Key will be used. | fluent-bit |
Topic_Key | If multiple Topics exists, the value of TopicKey in the record will indicate the topic to use. E.g: if Topic_Key is _router and the record is {"key1": 123, "router": "route2"}, Fluent Bit will use topic _route_2. Note that the topic must be registered in the Topics list. |
rdkafka.{property} |
The stdout output plugin allows to print to the standard output the data received through the input plugin. Their usage is very simple as follows:
We have specified to gather CPU usage metrics and print them out to the standard output in a human readable way:
No more, no less, it just works.
Stackdriver output plugin allows to ingest your records into Google Cloud Stackdriver Logging service.
Before to get started with the plugin configuration, make sure to obtain the proper credentials to get access to the service. We strongly recommend to use a common JSON credentials file, reference link:
Your goal is to obtain a credentials JSON file that will be used later by Fluent Bit Stackdriver output plugin.
If you are using a Google Cloud Credentials File, the following configuration is enough to get started:
Github reference: #761
An upstream connection error means Fluent Bit was not able to reach Google services, the error looks like this:
This belongs to a network issue by the environment where Fluent Bit is running, make sure that from the Host, Container or Pod you can reach the following Google end-points:
Stackdriver officially supports a logging agent based on Fluentd.
The td output plugin, allows to flush your records into the Treasure Data cloud service.
The plugin supports the following configuration parameters:
In order to start inserting records into Treasure Data, you can run the plugin from the command line or through the configuration file:
Ideally you don't want to expose your API key from the command line, using a configuration file is higly desired.
In your main configuration file append the following Input & Output sections:
Splunk output plugin allows to ingest your records into a Splunk Enterprise service through the HTTP Event Collector (HEC) interface.
To get more details about how to setup the HEC in Splunk please refer to the following documentation: Splunk / Use the HTTP Event Collector
Splunk output plugin supports TTL/SSL, for more details about the properties available and general configuration, please refer to the TLS/SSL section.
In order to insert records into a Splunk service, you can run the plugin from the command line or through the configuration file:
The splunk plugin, can read the parameters from the command line in two ways, through the -p argument (property), e.g:
In your main configuration file append the following Input & Output sections:
By default, the Splunk output plugin nests the record under the event key in the payload sent to the HEC. It will also append the time of the record to a top level time key.
If you would like to customize any of the Splunk event metadata, such as the host or target index, you can set Splunk_Send_Raw On in the plugin configuration, and add the metadata as keys/values in the record. Note: with Splunk_Send_Raw enabled, you are responsible for creating and populating the event section of the payload.
For example, to add a custom index and hostname:
This will create a payload that looks like:
For more information on the Splunk HEC payload format and all event meatadata Splunk accepts, see here: http://docs.splunk.com/Documentation/Splunk/latest/Data/AboutHEC
Specify an HTTP Proxy. The expected format of this value is . Note that https is not supported yet.
{property} can be any
Key
Description
default
Format
Specify the data format to be printed. Supported formats are msgpack and json_lines.
msgpack
json_date_key
Specify the name of the date field in output
date
json_date_format
Specify the format of the date. Supported formats are double and iso8601 (eg: 2018-05-30T09:39:52.000681Z)
double
Key
Description
default
google_service_credentials
Absolute path to a Google Cloud credentials JSON file
Value of environment variable $GOOGLE_SERVICE_CREDENTIALS
service_account_email
Account email associated to the service. Only available if no credentials file has been provided.
Value of environment variable $SERVICE_ACCOUNT_EMAIL
service_account_secret
Private key content associated with the service account. Only available if no credentials file has been provided.
Value of environment variable $SERVICE_ACCOUNT_SECRET
resource
Set resource type of data. Only global is supported.
global
Key
Description
Default
API
The Treasure Data API key. To obtain it please log into the Console and in the API keys box, copy the API key hash.
Database
Specify the name of your target database.
Table
Specify the name of your target table where the records will be stored.
Region
Set the service region, available values: US and JP
US
Key
Description
default
Host
IP address or hostname of the target Splunk service.
127.0.0.1
Port
TCP port of the target Splunk service.
8088
Splunk_Token
Specify the Authentication Token for the HTTP Event Collector interface.
Splunk_Send_Raw
When enabled, the record keys and values are set in the top level of the map instead of under the event key.
Off
HTTP_User
Optional username for Basic Authentication on HEC
HTTP_Passwd
Password for user defined in HTTP_User