Configure distribution metrics

This page explains how to create distribution-type log-based metrics using the Google Cloud console, the Logging API, and the Google Cloud CLI. For an overall view of log-based metrics, go to Overview of log-based metrics.

Overview

Distribution metrics require both a filter to select the relevant log entries and a value extractor to grab the numeric value for the distribution. The value extractor is the same kind as is used for user-defined labels.

A distribution metric records the statistical distribution of the extracted values in histogram buckets. The extracted values are not recorded individually, but their distribution across the configured buckets are recorded, along with the count, mean, and sum of squared deviation of the values. You can use the default layout of histogram buckets in your distribution or you can fine-tune the buckets' boundaries to approximately capture the values.

For more information on viewing and interpreting distribution metrics, see Distribution metrics.

Before you begin

To use log-based metrics, you must have a Google Cloud project with billing enabled:
Ensure that your Identity and Access Management role includes the permissions required to create and view log-based metrics, and to create alerting policies. For details, see Permissions for log-based metrics.

Create a distribution metric

The metric counts the log entries identified by a filter you provide. You can use regular expressions in your filter, and we recommend that you include a resource type. The length of a filter can't exceed 20,000 characters.

Don't put sensitive information in the filter. Filters are treated as service data.

Console

Follow these steps to create a log-based counter metric in the Google Cloud console in your Google Cloud project:

In the Google Cloud console, go to the Log-based Metrics page:
Go to Log-based Metrics

If you use the search bar to find this page, then select the result whose subheading is Logging.
Click Create Metric. The Create logs metric panel appears.
Set the Metric type: Select Distribution.
Set the following fields in the Details section:
- Log metric name: Choose a name that is unique among the log-based metrics in your Google Cloud project. Some naming restrictions apply; see Troubleshooting for details.
- Description: Enter a description for the metric.
- Units: (Optional) For distribution metrics, you can optionally enter units, such as s and ms. For more information, see the unit field of the MetricDescriptor.
Define your metric filter in the Filter selection section.
1. Use the Select project or log bucket menu to select whether the metric counts the log entries in your Google Cloud project or only those log entries in a specific log bucket.
2. Create a filter that collects only the log entries that you want to count in your metric using the logging query language. You can also use regular expressions to create your metric's filters.
3. Field name: Enter the log entry field that contains the distribution's value. You are offered choices as you type. For example:
```
protoPayload.latency
```
4. Regular expression: (Optional) If Field name always contains a numeric value convertible to type double, then you can leave this field empty. Otherwise, specify a regular expression that extracts the numeric distribution value from the field value.
  
  Example. Suppose that your latency log entry field contains a number followed by ms for milliseconds. The following regexp chooses the number without the unit suffix:
```
([0-9.]+)
```
  The parentheses, known as a regexp capture group, identifies the part of the text match that will be extracted. See using regular expressions for details.
- Advanced (Histogram buckets): (Optional) Clicking Advanced opens a section of the form you can use to specify custom bucket layouts. If you don't specify your bucket layouts, a default bucket layout is provided. For more information, see Histogram buckets on this page.
1. To see which log entries match your filter, click Preview logs.
(Optional) Add a label in the Labels section. For instructions on creating labels, see Create a label.
Click Create metric to create the metric.

gcloud

To create a distribution-type log-based metric, create a file that contains a representation of your LogMetric definition in JSON or YAML format. Then use the following command to read the configuration from your file:

gcloud logging metrics create METRIC_NAME --config-from-file FILENAME

For information about describing the histogram buckets for a distribution, see Histogram buckets.

API

To create a distribution metric, use the projects.metrics.create method of the Logging API. If you use the APIs Explorer pane on the reference page, then prepare the arguments as follows:

Set the parent field to the project or bucket in which the metric is to be created:
- For a project-scoped log-based metric, specify the project:
```
projects/PROJECT_ID
```
- For a bucket-scoped log-based metric, specify the bucket:
```
projects/PROJECT_ID/locations/LOCATION/bucket/BUCKET_ID
```

Set the request body to a LogMetric object. Following is a sample object for a distribution metric.

{
  name:        "my-metric"
  description: "Description of my-metric."
  filter:      "resource.type=gce_instance AND log_id(\"syslog\")",
  valueExtractor: "REGEXP_EXTRACT(jsonPayload.latencyField, \"([0-9.]+)ms\")",

  labelExtractors: {
    "my-label-1":
      "REGEXP_EXTRACT(jsonPayload.someField, \"before ([[:word:]]+) after\")",
    "my-label-2":
      "EXTRACT(jsonPayload.anotherField, \"before ([0-9]+) after\")",
  },
  bucketOptions: { [SEE_BELOW] },

  metricDescriptor: {
      metricKind: DELTA,
      valueType: DISTRIBUTION,
      unit: "ms",

      labels: [
        {
          key: "my-label-1",
          valueType: STRING,
          description: "Description of string my-label-1.",
        },
        {
          key: "my-label-2",
          valueType: INT64,
          description: "Description of integer my-label-2.",
        }
      ]
  },
}

Notes:

Some naming restrictions apply; see Troubleshooting for details.
metricDescriptor: a MetricDescriptor object. metricKind must be DELTA. valueType must be DISTRIBUTION.

Histogram buckets

Distribution metrics include a histogram that counts the number of values that fall in specified ranges (buckets). You can have up to 200 buckets in a distribution metric.

Each bucket has two boundary values, L and H, that define the lowest and highest values covered by the bucket. The width of the bucket is H - L. Since there cannot be gaps between buckets, the lower boundary of one bucket is the same as the higher boundary of the previous bucket, and so forth. So that the boundaries don't fall into more than one bucket, a bucket includes its lower boundary; its higher boundary belongs to the next bucket.

All bucket layouts can be specified by listing, in increasing order, the boundary values between individual buckets. The first bucket is the underflow bucket, which counts values less than the first boundary. The last bucket is the overflow bucket, which counts values greater than or equal to the last boundary. The other buckets count values greater than or equal to their lower boundary and less than their upper boundary. If there are n boundary values, then there are n+1 buckets. Excluding the underflow and overflow buckets, there are n-1 finite buckets.

There are three different ways to specify the boundaries between histogram buckets for distribution metrics. You either specify a formula for the boundary values, or you list the boundary values:

Linear(offset, width, i): Every bucket has the same width. The boundaries are offset + width * i, for i=0,1,2,...,N. For more information on linear buckets, see the API reference.
Exponential(scale, growth_factor, i): Bucket widths increase for higher values. The boundaries are scale * growth_factorⁱ, for i=0,1,2,...,N. For more information on exponential buckets, see the API reference.
Explicit: You list all the boundaries for the buckets in the bounds array. Bucket i has these boundaries:
```
Upper bound: bounds[*i*] for (0 <= *i* < *N*-1)
Lower bound: bounds[*i* - 1] for (1 <= *i* < *N*)
```
For more information on explicit buckets, see the API reference.

How you specify your histogram buckets is explained in the following section:

Console

The Histogram buckets submenu opens when you create a distribution metric and you click More in the Metric editor form. The following subform is for the Linear bucket layout:

Histogram buckets

Linear buckets: Fill in the histogram bucket form as follows.

Type: Linear
Start value (a): The lower boundary of the first finite bucket. This value is called offset in the API.
Number of buckets (N): The number of finite buckets. The value must be greater than or equal to 0.
Bucket width (b): The difference between the upper bound and lower bound in each finite bucket. The value must be greater than 0.

For example, if the start value is 5, the number of buckets is 4, and the bucket width is 15, then the bucket ranges are as follows:

(-INF, 5), [5, 20), [20, 35), [35, 50), [50, 65), [65, +INF)

Explicit buckets: Fill in the histogram bucket form as follows:

Type: Explicit
Bounds (b): A comma-separated list of the boundary values of the finite buckets. This also determines the number of buckets and their widths.

For example, if the list of boundaries is:

0, 1, 2, 5, 10, 20

then there are five finite buckets with the following ranges:

(-INF, 0), [0, 1), [1, 2), [2,5), [5, 10), [10, 20), [20, +INF)

Exponential buckets: Fill in the histogram bucket form as follows:

Type: Exponential
Number of buckets (N): The total number of finite buckets. The value must be greater than 0.
Linear scale (a): The linear scale for the buckets. The value must be greater than 0.
Exponential growth factor (b): The exponential growth factor for the buckets. The value must be greater than 1.

For example, if N=4, a=3, and b=2, then the bucket ranges are as follows:

(-INF, 3), [3, 6), [6, 12), [12, 24), [24, 48), [48, +INF)

For more information about the buckets, see BucketOptions in the Cloud Monitoring API.

API

The optional bucket layout is specified by the bucketOptions field in the LogMetric object supplied to projects.metrics.create. For the complete LogMetric object, see Create a distribution metric on this page. The additions for bucket layouts are as shown:

Linear buckets:

{ # LogMetric object
  ...
  bucketOptions: {
    linearBuckets: {
      numFiniteBuckets: 4,
      width: 15,
      offset: 5
    }
  },
  ...
}

The previous sample creates the following buckets:

(-INF, 5), [5, 20), [20, 35), [35, 50), [50, 65), [65, +INF)

Explicit buckets: Boundaries are listed individually.

{ # LogMetric object
  ...
  bucketOptions: {
    explicitBuckets: {
      bounds: [0, 1, 2, 5, 10, 20 ]
    }
  },
  ...
}

The previous sample creates the following buckets:

(-INF, 0), [0, 1), [1, 2), [2, 5), [5, 10), [10, 20), [20, +INF)

Exponential buckets: Boundaries are scale * growthFactor ^ i, for i=0,1,2, ..., numFiniteBuckets

{ # LogMetric object
  ...
  bucketOptions: {
    exponentialBuckets: {
      numFiniteBuckets: 4,
      growthFactor: 2,
      scale: 3
    }
  },
  ...
}

The previous sample creates the following buckets:

(-INF, 3), [3, 6), [6, 12), [12, 24), [24, 48), [48, +INF)

New metric latency

Your new metric appears in the list of metrics and in the relevant Monitoring menus right away. However, it might take up to a minute for the metric to start collecting data for the matching log entries.

Inspect distribution metrics

To list the user-defined log-based metrics in your Google Cloud project or to inspect a particular metric in your Google Cloud project, do the following:

Console

In the Google Cloud console, go to the Log-based Metrics page:
Go to Log-based Metrics

If you use the search bar to find this page, then select the result whose subheading is Logging.
In the User-defined metrics pane, you see the user-defined log-based metrics in the current Google Cloud project:
To view the data in a log-based metric, click the Menu in the metric's row and select View in Metrics Explorer.

gcloud

To list the user-defined log-based metrics in your Google Cloud project, use the following command:

gcloud logging metrics list

To display a user-defined log-based metric in your Google Cloud project, use the following command:

gcloud logging metrics describe METRIC_NAME

To get help, use the following command:

gcloud logging metrics --help

You can't read a metric's time series data from the Google Cloud CLI.

API

List metrics

To list the user-defined log-based metrics in a Google Cloud project, use the projects.metrics.list API method. Fill in the parameters to the method as follows:

parent: The resource name of the Google Cloud project: projects/PROJECT_ID.
pageSize: The maximum number of results.
pageToken: Gets the next page of results. For information about using page tokens, see projects.metrics.list.

Retrieve metric definitions

To retrieve a single user-defined log-based metric, use the projects.metrics.get API method. Fill in the parameters to the method as follows:

metricName: The resource name of the metric:
```
projects/PROJECT_ID/metrics/METRIC_ID
```

Read metric data

To read the time series data in a log-based metric, use the projects.timeseries.list in the Cloud Monitoring API. For details on time series data, see Reading time series.

To read a single user-defined log-based metric, fill in the method's parameters with this metric type and identifier:

logging.googleapis.com/user/METRIC_ID

Update distribution metrics

You can edit a user-defined log-based metric to change its description, filter, and the names of fields referenced in the metric. You can add new labels to the metric and you can change the regular expressions used to extract values for the metric and its labels. If you're using a bucket-scoped metric, you can also update the metric's bucket.

You can't change the names or types of user-defined log-based metrics or their labels, and you can't delete existing labels in a log-based metric.

To edit a log-based metric, do the following:

Console

In the Google Cloud console, go to the Log-based Metrics page:
Go to Log-based Metrics

If you use the search bar to find this page, then select the result whose subheading is Logging.
Click Edit metric in the Menu for the log-based metric that you want to modify.
Change the allowable items in the metric.
Click Update metric.

gcloud

Use the Google Cloud CLI to change a counter metric's description, filter query and bucket. You can update any or all of the fields at once.

gcloud logging update METRIC_NAME \
  --description="METRIC_DESCRIPTION" \
  --log-filter="FILTER" \
  --bucket-name=BUCKET_NAME

If you change the bucket associated with a bucket-scoped metric, then any metric data collected before the change no longer reflects the current configuration. The metric data collected for the previous bucket is not removed.

To update distribution metrics or other counter metric fields, excluding the METRIC_NAME, create a file that contains the revised specification of your LogMetric in JSON or YAML format. Then, update the metric by calling the update command with the --config-from-file field, replacing FILENAME with the name of your JSON or YAML file:

gcloud logging update METRIC_NAME --config-from-file FILENAME

For more details, use the following command:

gcloud logging metrics update --help

API

To edit a log-based metric, use the projects.metrics.update method in the API. Set the fields as follows:

metricName: The full resource name of the metric:

projects/PROJECT_ID/metrics/METRIC_ID

For example:

projects/my-gcp-project/metrics/my-error-metric

In the request body, include a LogMetric object that is exactly the same as the existing metric except for the changes and additions you want to make.

Delete distribution metrics

To delete a user-defined log-based metric, do the following:

Console

In the Google Cloud console, go to the Log-based Metrics page:
Go to Log-based Metrics

If you use the search bar to find this page, then select the result whose subheading is Logging.
Select the metric you want to delete and click Delete.

Alternatively, click Delete metric in the menu of the log-based metric that you want to delete.

gcloud

Use the following command to delete a user-defined log-based metric in the current Google Cloud project:

gcloud logging metrics delete METRIC_NAME

For more details, use the following command:

gcloud logging metrics delete --help

API

To delete a user-defined log-based metric, use the projects.metrics.delete method in the API.

In addition, in the Google Cloud console Log-based metric page, the User-defined metrics pane of the log-based metrics interface provides more features to help you manage the user-defined metrics on your Google Cloud project. See User-defined metrics for details.