Using Custom Metrics

This guide describes how to create and use custom metrics. The information is divided into the following sections:

  • Custom metrics with OpenCensus describes how to use OpenCensus, an open-source monitoring and tracing library, to create custom metrics, add metric data to them, and export them to Stackdriver Monitoring.

    When metrics from OpenCensus are exported to Stackdriver Monitoring, Monitoring treats them like any other custom metrics.

  • Creating custom metrics describes how to use the Stackdriver Monitoring API to create custom metrics and to add time series data to them.

    The Monitoring API is illustrated with examples using the API Explorer, C#, Go, Java, Node.js, PHP, Python, and Ruby programming languages.

The following information applies to both custom metrics and the metrics provided by Stackdriver Monitoring:

  • Browsing metrics explains how to list and examine your custom metrics and the over 900 built-in metrics.
  • Reading metrics explains how to retrieve time series data from custom and built-in metrics using the Monitoring API. You can also use metric data in charts and alerts.

All of these operations on metrics require the Stackdriver Monitoring API v3. See Introduction to the Stackdriver Monitoring API for reference documentation.

For a discussion of concepts underlying metrics in Stackdriver Monitoring, see Metrics, time series, and resources.

Before you begin

Custom metrics belong to Google Cloud Platform projects that are members of a Workspace. Even if you are only browsing the built-in metrics, you need a project to work from:

  1. Create or select a Google Cloud Platform Console project whose monitoring data you want to access. In this guide, the ID for your project is referred to as {your-project-id}.
  2. Enable your project for Monitoring.

If you want to set up metrics based on Stackdriver logs in your GCP projects, use logs-based metrics.

About custom metrics

Custom metrics are the same as Monitoring's built-in metrics, except:

  • You can create custom metrics within your GCP projects.
  • Custom metric names typically begin, which differs from the built-in metrics.
  • You can write time series data to your custom metrics.
  • You can delete your custom metrics.

See the Metrics list for details about the built-in metrics.

The following table shows which methods in the Monitoring API can be used with custom metrics and with built-in metrics:

Monitoring API API method Use with
custom metrics
Use with
built-in metrics
monitoredResourceDescriptors.get yes yes
monitoredResourceDescriptors.list yes yes
metricDescriptors.get yes yes
metricDescriptors.list yes yes
timeSeries.list yes yes
timeSeries.create yes
metricDescriptors.create yes
metricDescriptors.delete yes

Limits and latencies

See Quotas and limits for limits on the number of custom metrics and the number of active time series, and for the data retention period. If you wish to keep your metric data beyond the retention period, you must manually copy the data to another location, such as Cloud Storage or BigQuery.

For information about latencies associated with writing data to custom metrics, see Latency of metric data.

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