Using dashboards and charts

Dashboards are one way for you to view and analyze metric data that is important to you. Cloud Monitoring provides predefined dashboards for the resources and services that you use. These dashboards require no setup or configuration effort.

Cloud Monitoring provides predefined dashboards for Google Cloud services, and it provides the ability to create custom dashboards. With custom dashboards, you determine which charts are displayed and their configuration. You can create custom dashboards by using the Google Cloud Console or by using the Dashboard endpoint in the Cloud Monitoring API.

This page describes the quotas and limits applicable to dashboards, the authorization necessary to create charts and dashboards, and how you can improve the performance of your charts and dashboards.

  • For information about using the Google Cloud Console to manage your dashboards, see Managing dashboards through the console.
  • For information about using the Cloud Monitoring API to manage your dashboards, see Managing dashboards by API .
  • Cloud Monitoring also provides a GitHub repository of dashboard configurations for monitoring a selection of Google Cloud services. These dashboard configuration can also be installed using the API. For more information, see Installable dashboards.

Quotas and limits

The following limits apply to dashboards and charts:

Category Value
Dashboards per Workspace 1000
Charts on a dashboard 25
Lines on a chart 300

Authorization

This section describes the roles or permissions needed to create a dashboard or to add charts to a dashboard. For detailed information about Cloud Identity and Access Management (Cloud IAM) for Cloud Monitoring, see Access control.

Each Cloud IAM role has an ID and a name. Role IDs have the form roles/monitoring.editor and are passed as arguments to the gcloud command-line tool when configuring access control. For more information, see Granting, changing, and revoking access. Role names, such as Monitoring Editor, are displayed by the Cloud Console.

Required Cloud Console roles

To create a dashboard or to add charts to a dashboard, your Cloud IAM role name for the Google Cloud project must be one of the following:

  • Monitoring Editor
  • Monitoring Admin
  • Project Owner

To view a list of roles and their associated permissions, see Roles.

Required API permissions

To use the Cloud Monitoring API to create a dashboard or to add charts to a dashboard, your Cloud IAM role ID for the Google Cloud project must be one of the following:

  • roles/monitoring.dashboardEditor: This role ID grants the minimal permissions that are needed to create a dashboard or to add charts to a dashboard. For more details on this role, see Predefined dashboard roles.
  • role/monitoring.editor
  • role/monitoring.admin
  • role/owner

To identify the permission required for a specific Cloud Monitoring API method, see Cloud Monitoring API permissions. To view a list of roles and their associated permissions, see Roles.

Determining your role

To determine your role for a project by using the Cloud Console, do the following:

  1. Open the Cloud Console and select the Google Cloud project:

    Go to Cloud Console

  2. To view your role, click IAM & admin. Your role is on the same line as your username.

To determine your organization-level permissions, contact your organization's administrator.

Performance of dashboards and charts

The performance of a chart is sensitive to the number of time series to be displayed. The number of time series depends, in part, on the structure of the metric type and monitored-resource type associated with the time series. Each of these types has a number of labels; the Metrics list and Monitored resource list include the labels for each metric and monitored-resource type.

There is one time series for each unique combination of values for the set of labels. The number of possible combinations is called the cardinality. For more information on labels, values, and cardinality, see Cardinality.

If you encounter performance issues when displaying metric data, you can often mitigate the issues by using one of the techniques:

  • Removing unnecessary information by filtering.
  • Collapsing related information together by combining time series.
  • Focusing on unusual data with outlier mode.
  • Reducing the cardinality of a custom metric by reducing the number of labels or the range of values possible for a label.