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Documentation Grafana Agent Flow mode Concepts Modules

Modules

Modules are a way to create Grafana Agent Flow configurations which can be loaded as a component. Modules are a great way to parameterize a configuration to create reusable pipelines.

Modules are Grafana Agent Flow configurations which have:

• Arguments: settings which configure a module.
• Exports: named values which a module exposes to the consumer of the module.
• Components: Grafana Agent Flow Components to run when the module is running.

Modules are loaded into Grafana Agent Flow by using a Module loader.

Refer to the documentation for the argument block and export block to learn how to define arguments and exports for a module.

Module loaders

A Module loader is a Grafana Agent Flow component which retrieves a module and runs the components defined inside of it.

Module loader components are responsible for:

• Retrieving the module source to run.
• Creating a Component controller for the module to run in.
• Passing arguments to the loaded module.
• Exposing exports from the loaded module.

Module loaders typically are called module.LOADER_NAME. The list of module loader components can be found in the list of Grafana Agent Flow Components.

Some module loaders may not support running modules with arguments or exports; refer to the documentation for the module loader you are using for more information.

Module sources

Modules are designed to be flexible, and can have their configuration retrieved from anywhere, such as:

• The local filesystem
• An S3 bucket
• An HTTP endpoint

Each module loader component will support different ways of retrieving module sources. The most generic module loader component, module.string, can load modules from the export of another Flow component:

river Copy

local.file "my_module" {
  filename = "PATH_TO_MODULE"
}

module.string "my_module" {
  content = local.file.my_module.content

  arguments {
    MODULE_ARGUMENT_NAME_1 = MODULE_ARGUMENT_VALUE_1
    MODULE_ARGUMENT_NAME_2 = MODULE_ARGUMENT_VALUE_2
    // ...
  }
}

Example module

This example module manages a pipeline which filters out debug- and info-level log lines which are given to it:

river Copy

// argument.write_to is a required argument which specifies where filtered
// log lines should be sent.
//
// The value of the argument can be retrieved in this file with
// argument.write_to.value.
argument "write_to" {
  optional = false
}

// loki.process.filter is our component which executes the filtering, passing
// filtered logs to argument.write_to.value.
loki.process "filter" {
  // Drop all debug- and info-level logs.
  stage.match {
    selector = "{job!=\"\"} |~ \"level=(debug|info)\""
    action   = "drop"
  }

  // Send processed logs to our argument.
  forward_to = argument.write_to.value
}

// export.filter_input exports a value to the consumer of the module.
export "filter_input" {
  // Expose the receiver of loki.process so the module consumer can send
  // logs to our loki.process component.
  value = loki.process.filter.receiver
}

It can then be used as a processing step before writing logs to Loki:

river Copy

loki.source.file "self" {
  targets = LOG_TARGETS

  // Forward collected logs to the input of our filter.
  forward_to = [module.string.filter.exports.logs_input]
}

module.file "log_filter" {
  filename = "/path/to/modules/log_filter.river"

  arguments {
    // Configure the filter to forward filtered logs to loki.echo below.
    logs_output = [loki.write.default.receiver],
  }
}

loki.write "default" {
  endpoint {
    url = "LOKI_URL"
  }
}