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Documentation Grafana Alloy Reference Components otelcol otelcol.exporter.googlecloud

Community

otelcol.exporter.googlecloud

Community: This component is developed, maintained, and supported by the Alloy user community. Grafana doesn’t offer commercial support for this component. To enable and use community components, you must set the --feature.community-components.enabled flag to true.

otelcol.exporter.googlecloud accepts metrics, traces, and logs from other otelcol components and sends it to Google Cloud.

You can specify multiple otelcol.exporter.googlecloud components by giving them different labels.

Usage

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otelcol.exporter.googlecloud "<LABEL>" {
}

Authenticating

Refer to the original Google Cloud Exporter document.

Arguments

You can use the following arguments with otelcol.exporter.googlecloud:

Blocks

You can use the following blocks with otelcol.exporter.googlecloud:

The > symbol indicates deeper levels of nesting. For example, metric > experimental_wal refers to a experimental_wal block defined inside a metric block.

debug_metrics

The debug_metrics block configures the metrics that this component generates to monitor its state.

The following arguments are supported:

disable_high_cardinality_metrics is the Grafana Alloy equivalent to the telemetry.disableHighCardinalityMetrics feature gate in the OpenTelemetry Collector. It removes attributes that could cause high cardinality metrics. For example, attributes with IP addresses and port numbers in metrics about HTTP and gRPC connections are removed.

impersonate

The following arguments are supported:

log

The following arguments are supported:

metric

The following arguments are supported:

experimental_wal

The following arguments are supported:

sending_queue

The sending_queue block configures an in-memory buffer of batches before data is sent to the HTTP server.

The following arguments are supported:

When enabled is true, data is first written to an in-memory buffer before sending it to the configured server. Batches sent to the component’s input exported field are added to the buffer as long as the number of unsent batches doesn’t exceed the configured queue_size.

queue_size determines how long an endpoint outage is tolerated. Assuming 100 requests/second, the default queue size 1000 provides about 10 seconds of outage tolerance. To calculate the correct value for queue_size, multiply the average number of outgoing requests per second by the time in seconds that outages are tolerated. A very high value can cause Out Of Memory (OOM) kills.

The num_consumers argument controls how many readers read from the buffer and send data in parallel. Larger values of num_consumers allow data to be sent more quickly at the expense of increased network traffic.

If an otelcol.storage.* component is configured and provided in the queue’s storage argument, the queue uses the provided storage extension to provide a persistent queue and the queue is no longer stored in memory. Any data persisted will be processed on startup if Alloy is killed or restarted. See the exporterhelper documentation in the OpenTelemetry Collector repository for more details.

trace

Exported fields

The following fields are exported and can be referenced by other components:

input accepts otelcol.Consumer data for any telemetry signal (metrics, logs, or traces).

Component health

otelcol.exporter.googlecloud is only reported as unhealthy if given an invalid configuration.

Debug information

otelcol.exporter.googlecloud doesn’t expose any component-specific debug information.

Example

This example scrapes logs from local files through a receiver for conversion to OpenTelemetry format before finally sending them to Cloud Logging.

This configuration includes the recommended memory_limiter and batch plugins, which avoid high latency for reporting telemetry, and ensure that the collector itself will stay stable (not run out of memory) by dropping telemetry if needed.

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Expand code

local.file_match "logs" {
  path_targets = [{
    __address__ = "localhost",
    __path__    = "/var/log/{syslog,messages,*.log}",
    instance    = constants.hostname,
    job         = "integrations/node_exporter",
  }]
}

loki.source.file "logs" {
  targets    = local.file_match.logs.targets
  forward_to = [otelcol.receiver.loki.gcp.receiver]
}

otelcol.receiver.loki "gcp" {
  output {
    logs = [otelcol.processor.memory_limiter.gcp.input]
  }
}

otelcol.processor.memory_limiter "gcp" {
  check_interval = "1s"
  limit = "200MiB"

  output {
    metrics = [otelcol.processor.batch.gcp.input]
    logs = [otelcol.processor.batch.gcp.input]
    traces = [otelcol.processor.batch.gcp.input]
  }
}

otelcol.processor.batch "gcp" {
  output {
    metrics = [otelcol.exporter.googlecloud.default.input]
    logs = [otelcol.exporter.googlecloud.default.input]
    traces = [otelcol.exporter.googlecloud.default.input]
  }
}

otelcol.exporter.googlecloud "default" {
  project = "my-gcp-project"
  log {
    default_log_name = "opentelemetry.io/collector-exported-log"
  }
}

Compatible components

otelcol.exporter.googlecloud has exports that can be consumed by the following components:

• Components that consume OpenTelemetry otelcol.Consumer