Fluentd and MongoDB Integration

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 MongoDB Plugin allows you to send metrics to a MongoDB 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.

MongoDB

This plugin sends metrics to MongoDB, automatically creating time series collections where they don’t already exist. Time series collections require MongoDB 5.0+.

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",
  ]

MongoDB

[[outputs.mongodb]]
              # connection string examples for mongodb
              dsn = "mongodb://localhost:27017"
              # dsn = "mongodb://mongod1:27017,mongod2:27017,mongod3:27017/admin&replicaSet=myReplSet&w=1"

              # overrides serverSelectionTimeoutMS in dsn if set
              # timeout = "30s"

              # default authentication, optional
              # authentication = "NONE"

              # for SCRAM-SHA-256 authentication
              # authentication = "SCRAM"
              # username = "root"
              # password = "***"

              # for x509 certificate authentication
              # authentication = "X509"
              # tls_ca = "ca.pem"
              # tls_key = "client.pem"
              # # tls_key_pwd = "changeme" # required for encrypted tls_key
              # insecure_skip_verify = false

              # database to store measurements and time series collections
              # database = "telegraf"

              # granularity can be seconds, minutes, or hours.
              # configuring this value will be based on your input collection frequency.
              # see https://docs.mongodb.com/manual/core/timeseries-collections/#create-a-time-series-collection
              # granularity = "seconds"

              # optionally set a TTL to automatically expire documents from the measurement collections.
              # ttl = "360h"

Input and output integration examples

Fluentd

1. 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.
2. 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.
3. Custom Plugin ID: Implement the @id parameter in your Fluentd configuration to maintain a consistent plugin_id, which helps avoid issues with high series cardinality during frequent restarts.

MongoDB

1. Log Management: Integrate this plugin to send application logs directly to MongoDB for structured storage and flexible querying. You can analyze logs as time series data, aggregating logs by hour, day, or month.

2. Metric Capture: Use the plugin to capture system metrics (CPU, memory usage) in real-time and store them in MongoDB. The time-series collections will allow for efficient queries over time ranges.

3. Monitoring Solutions: Combine this output plugin with inputs from various sources, such as disk usage metrics, network statistics, or application performance data. It allows for consolidated monitoring dashboards with historical trends saved in MongoDB.

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.