Metrics definitions
Metrics are defined in YAML files located in subfolders of config/metrics
and ee/config/metrics
.
The YAML files are called metrics definitions.
This page describes the subsection of metric definitions with data_source: internal_events
.
You can find a general overview of metric definition files in the Metric Dictionary Guide
Supported metric types
Internal events supports three different metric types which are grouped like this:
- All time total counters
- Time framed total counters
- Time framed unique counters
Count type / Time frame |
7d / 28d
| all
|
---|---|---|
Total count | Time framed total counters | All time total counters |
Unique count | Time framed unique counters |
You can tell if a metric is counting unique values or total values by looking at the event selection rules.
A snippet from a unique metric could look like below. Notice the unique
property which defines which identifier of the create_merge_request
event is used for counting the unique values.
events:
- name: create_merge_request
unique: user.id
Similarly, a snippet from a total count metric can look like below. Notice how there is no unique
property.
events:
- name: create_merge_request
We can track multiple events within one metric via aggregated metrics.
All time total counters
Example: Total visits to /groups/:group/-/analytics/productivity_analytics all time
data_category: optional
key_path: counts.productivity_analytics_views
description: Total visits to /groups/:group/-/analytics/productivity_analytics all time
product_group: optimize
value_type: number
status: active
time_frame: all
data_source: internal_events
events:
- name: view_productivity_analytics
distribution:
- ee
tier:
- premium
- ultimate
performance_indicator_type: []
milestone: "<13.9"
The combination of time_frame: all
and the event selection rule under events
referring to the
view_productivity_analytics
event means that this is an “all time total count” metric.
Time framed total counters
An example is: Weekly count of Runner usage CSV report exports
key_path: counts.count_total_export_runner_usage_by_project_as_csv_weekly
description: Weekly count of Runner usage CSV report exports
product_group: runner
performance_indicator_type: []
value_type: number
status: active
milestone: '16.9'
introduced_by_url: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/142328
data_source: internal_events
data_category: optional
distribution:
- ee
tier:
- ultimate
time_frame: 7d
events:
- name: export_runner_usage_by_project_as_csv
The combination of time_frame: 7d
and the event selection rule under events
referring to the
export_runner_usage_by_project_as_csv
event means that this is a “timed framed total count” metric.
Time framed unique counters
Example: Count of distinct users who opted to filter out anonymous users on the analytics dashboard view in the last 28 days.
key_path: count_distinct_user_id_from_exclude_anonymised_users_28d
description: Count of distinct users who opted to filter out anonymous users on the analytics dashboard view in the last 28 days.
product_group: platform_insights
performance_indicator_type: []
value_type: number
status: active
milestone: '16.7'
introduced_by_url: https://gitlab.com/gitlab-org/gitlab/-/merge_requests/138150
time_frame: 28d
data_source: internal_events
data_category: optional
distribution:
- ee
tier:
- ultimate
events:
- name: exclude_anonymised_users
unique: user.id
The combination of time_frame: 28d
, the event selection rule under events
referring to the
exclude_anonymised_users
event and the unique value (unique: user.id
) means that this is a “timed framed unique count” metric.
Event Selection Rules
Event selection rules are the parts which connects metric definitions and event definitions. They are needed to know which metrics should be updated when an event is triggered.
Each internal event based metric should have a least one event selection rule with the following properties.
Property | Required | Additional information |
---|---|---|
name
| yes | Name of the event |
unique
| no | Used if the metric should count the distinct number of users, projects, namespaces, or count the unique values for additional properties present in the event. Valid values are user.id , project.id and namespace.id . Additionally label , property , and value may also be used in reference to any additional properties included with the event.
|
filter
| no | Used when only a subset of events should be included in the metric. Only additional properties can be used for filtering. |
An example of a single event selection rule which updates a unique count metric when an event called pull_package
with additional property label
with the value rubygems
occurs:
- name: pull_package
unique: user.id
filter:
label: rubygems
Filters
Filters are used to constrain which events cause an metric to increase.
This filter includes only pull_package
events with label: rubygems
:
- name: pull_package
filter:
label: rubygems
Whereas, this filter is even more restricted and only includes pull_package
events with label: rubygems
and property: deploy_token
:
- name: pull_package
filter:
label: rubygems
property: deploy_token
Filters only support matching of exact values and not wildcards or regular expressions.
Aggregated metrics
A metric definition with several event selection rules can be considered an aggregated metric.
If you want to get total number of pull_package
and push_package
events you have to add two event selection rules:
events:
- name: pull_package
- name: push_package
To get the number of unique users that have at least pushed or pulled a package once:
events:
- name: pull_package
unique: user.id
- name: push_package
unique: user.id
Notice that unique metrics and total count metrics cannot be mixed in a single metric.