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The output plugins defines where Fluent Bit should flush the information it gathers 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.
Datadog
Ingest logs into Datadog.
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
TCP & TLS
flush records to a TCP server.
Flush records to the Treasure Data cloud service for analytics.
NATS
flush records to a NATS server.
NULL
throw away events.
BigQuery output plugin is and experimental plugin that allows you to stream records into service. The implementation does not support the following, which would be expected in a full production version:
.
using insertId.
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:
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 |
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. |
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.
Output the records using a custom format template.
This accepts a formatting template and fills placeholders using corresponding values in a record.
For example, if you set up the configuration as below:
You will get the following output:
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:
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 |
Template | The format string. Default: '{time} {message}' |
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. |
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:
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 es output plugin, allows to flush your records into a Elasticsearch 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. Also see the FAQ below
Elasticsearch 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 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
Since Elasticsearch 6.0, you cannot create multiple types in a single index. This means that you cannot set up your configuration as below anymore.
If you see an error message like below, you'll need to fix your configuration to use a single type on each index.
Rejecting mapping update to [search] as the final mapping would have more than 1 type
For details, please read the official blog post on that issue.
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:
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:
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:
GELF is Graylog Extended Log Format. The GELF output plugin allows to send logs in GELF format directly to a Graylog input using TLS, TCP or UDP protocols.
The following instructions assumes that you have a fully operational Graylog server running in your environment.
According to GELF Payload Specification, there are some mandatory and optional fields which are used by Graylog in GELF format. These fields are determined with Gelf\*_Key_ key in this plugin.
GELF output plugin supports TLS/SSL, for more details about the properties available and general configuration, please refer to the TLS/SSL section.
If you're using Fluent Bit to collect Docker logs, note that Docker places your log in JSON under key log. So you can set log as your Gelf_Short_Message_Key to send everything in Docker logs to Graylog. In this case, you need your log value to be a string; so don't parse it using JSON parser.
The order of looking up the timestamp in this plugin is as follows:
Value of Gelf_Timestamp_Key provided in configuration
Value of timestamp key
If you're using Docker JSON parser, this parser can parse time and use it as timestamp of message. If all above fail, Fluent Bit tries to get timestamp extracted by your parser.
Timestamp does not set by Fluent Bit. In this case, your Graylog server will set it to the current timestamp (now).
Your log timestamp has to be in UNIX Epoch Timestamp format. If the Gelf_Timestamp_Key value of your log is not in this format, your Graylog server will ignore it.
If you're using Fluent Bit in Kubernetes and you're using Kubernetes Filter Plugin, this plugin adds host value to your log by default, and you don't need to add it by your own.
The version of GELF message is also mandatory and Fluent Bit sets it to 1.1 which is the current latest version of GELF.
If you use udp as transport protocol and set Compress to true, Fluent Bit compresses your packets in GZIP format, which is the default compression that Graylog offers. This can be used to trade more CPU load for saving network bandwidth.
If you're using Fluent Bit for shipping Kubernetes logs, you can use something like this as your configuration file:
By default, GELF tcp uses port 12201 and Docker places your logs in /var/log/containers directory. The logs are placed in value of the log key. For example, this is a log saved by Docker:
If you use Tail Input and use a Parser like the docker parser shown above, it decodes your message and extracts data (and any other present) field. This is how this log in stdout looks like after decoding:
Now, this is what happens to this log:
Fluent Bit GELF plugin adds "version": "1.1" to it.
The Nest Filter, unnests fields inside log key. In our example, it puts data alongside stream and time.
We used this data key as Gelf_Short_Message_Key; so GELF plugin changes it to short_message.
Kubernetes Filter adds host name.
Timestamp is generated.
Any custom field (not present in GELF Payload Specification) is prefixed by an underline.
Finally, this is what our Graylog server input sees:
The Datadog output plugin allows to ingest your logs into Datadog.
Before you begin, you need a Datadog account, a Datadog API key, and you need to activate Datadog Logs Management.
Get started quickly with this configuration file:
If you get a 403 Forbidden error response, double check that you have a valid Datadog API key and that you have activated Datadog Logs Management.
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 MessagePack (or JSON) format.
HTTP 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 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
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 tcp output plugin allows to send records to a remote TCP server. The payload can be formatted in different ways as required.
The following parameters are available to configure a secure channel connection through TLS:
Run the following in a separate terminal, netcat will start listening for messages on TCP port 5170
Start Fluent Bit
No more, no less, it just works.
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:
Stackdriver output plugin allows to ingest your records into 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:
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:
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 usage metrics and print them out to the standard output in a human readable way:
No more, no less, it just works.
Splunk output plugin allows to ingest your records into a 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 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 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:
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 kafka 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:
We have specified to gather usage metrics and send them in JSON lines mode to a remote end-point using netcat service, e.g:
Github reference:
Stackdriver officially supports a .
For more information on the Splunk HEC payload format and all event meatadata Splunk accepts, see here:
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
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 Unit Size specification.
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
Time format (based on strftime) to generate the second part of the Index name.
%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 _id for outgoing records. This prevents duplicate records when retrying ES.
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
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.
Send_options
Always send options (with "size"=count of messages)
False
Require_ack_response
Send "chunk"-option and wait for "ack" response from server. Enables at-least-once and receiving server can control rate of traffic. (Requires Fluentd v0.14.0+ server)
False
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
Unit
The unit of duration. (second/minute/hour/day)
minute
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
Match
Pattern to match which tags of logs to be outputted by this plugin
Host
IP address or hostname of the target Graylog server
127.0.0.1
Port
The port that your Graylog GELF input is listening on
12201
Mode
The protocol to use (tls, tcp or udp)
udp
Gelf_Short_Message_Key
A short descriptive message (MUST be set in GELF)
short_message
Gelf_Timestamp_Key
Your log timestamp (SHOULD be set in GELF)
timestamp
Gelf_Host_Key
Key which its value is used as the name of the host, source or application that sent this message. (MUST be set in GELF)
host
Gelf_Full_Message_Key
Key to use as the long message that can i.e. contain a backtrace. (Optional in GELF)
full_message
Gelf_Level_Key
Key to be used as the log level. Its value must be in standard syslog levels (between 0 and 7). (Optional in GELF)
level
Packet_Size
If transport protocol is udp, you can set the size of packets to be sent.
1420
Compress
If transport protocol is udp, you can set this if you want your UDP packets to be compressed.
true
Key
Description
Default
Host
Required - The Datadog server where you are sending your logs.
http-intake.logs.datadoghq.com
TLS
Required - End-to-end security communications security protocol. Datadog recommends leaving this on.
on
apikey
Required - Your Datadog API key.
dd_service
Recommended - The human readable name for your service generating the logs - the name of your application or database.
dd_source
Recommended - A human readable name for the underlying technology of your service. For example, postgres or nginx.
dd_tags
Optional - The tags you want to assign to your logs in Datadog.
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
Specify an HTTP Proxy. The expected format of this value is http://host:port. Note that https is not supported yet.
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 and gelf.
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 and iso8601 (eg: 2018-05-30T09:39:52.000681Z)
double
gelf_timestamp_key
Specify the key to use for timestamp in gelf format
gelf_host_key
Specify the key to use for the host in gelf format
gelf_short_messge_key
Specify the key to use as the short message in gelf format
gelf_full_message_key
Specify the key to use for the full message in gelf format
gelf_level_key
Specify the key to use for the level in gelf format
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. | 5170 |
Format | Specify the data format to be printed. Supported formats are msgpack json, json_lines and json_stream. | 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 , iso8601 (eg: 2018-05-30T09:39:52.000681Z) and epoch. | double |
Key | Description | Default |
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 |
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 and gce_instance are supported. | global, gce_instance |
Key | Description | default |
Format | Specify the data format to be printed. Supported formats are msgpack json, json_lines and json_stream. | 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, iso8601 (eg: 2018-05-30T09:39:52.000681Z) and epoch. | double |
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 Splunk service. | 127.0.0.1 |
Port | TCP port of the target Splunk service. | 8088 |
Splunk_Token |
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 |
Key | Description | default |
Format | Specify data format, options available: json, msgpack. | json |
Message_Key | Optional key to store the message |
Message_Key_Field | If set, the value of Message_Key_Field in the record will indicate the message key. If not set nor found in the record, Message_Key will be used (if set). |
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 Topic_Key in the record will indicate the topic to use. E.g: if Topic_Key is router and the record is {"key1": 123, "router": "route_2"}, Fluent Bit will use topic route_2. Note that if the value of Topic_Key is not present in Topics, then by default the first topic in the Topics list will indicate the topic to be used. |
rdkafka.{property} |
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:
Specify the Authentication for the HTTP Event Collector interface.
{property} can be any
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