Type to search.

Google Cloud Platform carbon metricset

Serverless Beta

Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud.

Availability

  • Beta

    This functionality is in beta and is not ready for production usage. For beta features, the design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features. Specific Support terms apply.

Serverless interfaces and procedures might differ from classic Elastic Stack deployments.

Stack Beta

The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats.

Availability

  • Beta

    This functionality is in beta and is not ready for production usage. For beta features, the design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features. Specific Support terms apply.

Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments.

This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.

Warning

This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.

The carbon metricset is designed to collect Carbon Footprint data from GCP BigQuery monthly cost detail table. BigQuery is a fully-managed, serverless data warehouse.

Cloud Carbon export to BigQuery enables you to export detailed Google Cloud carbon footprint data (such as carbon produced by tier and service) automatically throughout the month to a BigQuery dataset that you specify. Then you can access your Cloud Carbon data from BigQuery for detailed analysis using Metricbeat. Please see export carbon footprint data to BigQuery for more details on how to export carbon footprint data.

Metricset-specific configuration notes

  • dataset_id: (Required) Dataset ID that points to the top-level container which contains the actual carbon footprint tables.
  • table_pattern: (Optional) The name of the table where carbon footprint data is stored. Default to carbon_footprint.

Configuration example

YAML 
- module: gcp
  metricsets:
    - carbon
  period: 24h
  project_id: "your project id"
  credentials_file_path: "your JSON credentials file path"
  dataset_id: "dataset id"
  table_name: "table name"

Fields

For a description of each field in the metricset, see the exported fields section.

Here is an example document generated by this metricset:

JSON 
{
  "@timestamp": "2017-10-12T08:05:34.853Z",
    "cloud.account.id": "01475F-5B1080-1137E7",
    "cloud.project.id": "elastic-bi",
    "cloud.project.name": "elastic-containerlib-prod",
    "cloud.provider": "gcp",
    "event": {
      "dataset": "gcp.carbon",
      "duration": 115000,
      "module": "gcp"
    },
    "gcp": {
      "carbon": {
        "project_id": "containerlib-prod-12763",
        "project_name": "elastic-containerlib-prod",
        "service_id": "24E6-581D-38E5",
        "service_description": "BigQuery",
        "footprint.scope1":          4.044,
        "footprint.scope2.location": 1.797,
        "footprint.scope2.market":   null,
        "footprint.scope3":          2.337,
        "footprint.offsets":         null
      }
    },
    "metricset": {
      "name": "carbon",
      "period": 10000
    },
    "service": {
      "type": "gcp"
    }
}