Fluentd and Apache Inlong Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
Table of Contents
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
Input and output integration overview
The Fluentd Input Plugin gathers metrics from Fluentd’s in_monitor plugin endpoint. It provides insights into various plugin metrics while allowing for custom configurations to reduce series cardinality.
The Inlong plugin connects Telegraf to Apache InLong, enabling seamless transmission of collected metrics to an InLong instance.
Integration details
Fluentd
This plugin gathers metrics from the Fluentd plugin endpoint provided by the in_monitor plugin. It reads data from the /api/plugin.json resource and allows exclusion of specific plugins based on their type.
Apache Inlong
This Inlong plugin is designed to publish metrics to an Apache InLong instance, which facilitates the management of data streams in a scalable manner. Apache InLong provides a robust framework for efficient data transmission between various components in a distributed environment. By leveraging this plugin, users can effectively route and transmit metrics collected by Telegraf to their InLong data-proxy infrastructure. As a key component in a data pipeline, the Inlong Output Plugin helps ensure that data is consistently formatted, streamed correctly, and managed in compliance with the standards set by Apache InLong, making it an essential tool for organizations looking to enhance their data analytics and reporting capabilities.
Configuration
Fluentd
[[inputs.fluentd]]
## This plugin reads information exposed by fluentd (using /api/plugins.json endpoint).
##
## Endpoint:
## - only one URI is allowed
## - https is not supported
endpoint = "http://localhost:24220/api/plugins.json"
## Define which plugins have to be excluded (based on "type" field - e.g. monitor_agent)
exclude = [
"monitor_agent",
"dummy",
]
Apache Inlong
[[outputs.inlong]]
## Manager URL to obtain the Inlong data-proxy IP list for sending the data
url = "http://127.0.0.1:8083"
## Unique identifier for the data-stream group
group_id = "telegraf"
## Unique identifier for the data stream within its group
stream_id = "telegraf"
## Data format to output.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
# data_format = "influx"
Input and output integration examples
Fluentd
- Basic Configuration: Set up the Fluentd Input Plugin to gather metrics from your Fluentd instance’s monitoring endpoint, ensuring you are able to track performance and usage statistics.
- Excluding Plugins: Use the
exclude
option to ignore specific plugins’ metrics that are not necessary for your monitoring needs, streamlining data collection and focusing on what matters. - Custom Plugin ID: Implement the
@id
parameter in your Fluentd configuration to maintain a consistentplugin_id
, which helps avoid issues with high series cardinality during frequent restarts.
Apache Inlong
-
Real-time Metrics Monitoring: Integrating the Inlong plugin with a real-time monitoring dashboard allows teams to visualize system performance continuously. As metrics flow from Telegraf to InLong, organizations can create dynamic panels in their monitoring tools, providing instant insights into system health, resource utilization, and performance bottlenecks. This setup encourages proactive management and swift identification of potential issues before they escalate into critical failures.
-
Centralized Data Processing: Use the Inlong plugin to send Telegraf metrics to a centralized data processing pipeline that processes large volumes of data for analysis. By directing all collected metrics through Apache InLong, businesses can streamline their data workflows and ensure consistency in data formatting and processing. This centralized approach facilitates easier data integration with business intelligence tools and enhances decision-making through consolidated data insights.
-
Integration with Machine Learning Models: By feeding metrics collected through the Inlong Output Plugin into machine learning models, teams can enhance predictive analytics capabilities. For instance, metrics can be analyzed to predict system failures or performance trends. This application allows organizations to leverage historical data and infer future performance, helping them optimize resource allocation and minimize downtime using automated alerts based on model predictions.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration