Metric Fields Explained
1
Name
Enter a clear, descriptive name for your metric. This is what you and your team will see in dashboards (e.g., API Calls, Credits, Tokens, etc.).
Use a name that makes the metric’s purpose obvious to all users.
2
Code
Provide a unique identifier for the metric in
snake_case (e.g., api_calls).The code must be unique across all your metrics and cannot be changed later. Use only lowercase letters, numbers, and underscores.
3
Description
Optionally, add context for your team (e.g., Count of API calls made by the customer).
This field is for internal reference and helps clarify the metric’s intent.
4
Aggregation Type
Choose how you want to roll up event data into a metric. The aggregation type determines how values are calculated and displayed.
| Aggregation Type | Description | Supported Data Types |
|---|---|---|
| Count | Counts the number of events that occurred | Any |
| Sum | Adds up the values of a specified field | Number, Currency |
| Maximum | Takes the highest value of a specified field | Number, Currency, Date |
| Unique Count | Counts unique values of a specified field | String, Number, Currency |
| Latest | Uses the most recent value of a specified field | Any |
| Average | Calculates the mean value of a specified field | Number, Currency |
When you select an aggregation type (except Count), you must specify the Property Name and Property Type to aggregate.
5
Property Name & Property Type
For aggregation types other than Count, specify:
- Property Name: The event property to aggregate (e.g.,
amount). - Property Type: The data type of the property (Number, Currency, String, or Date).
Only compatible data types can be used for each aggregation type. For example, Sum and Average require Number or Currency properties.
6
Recurring Metric
Enable this if the metric should reset every billing period (e.g., monthly API call quotas).
This is useful for metrics that track usage against recurring limits.
7
Group By Properties
(optional) Enter a comma-separated list of event properties to break down the metric (e.g.,
region, instance_type).Use this to analyze usage by customer segment, region, or other dimensions.
8
Property Filters
(optional) Add filters to include or exclude events based on property values (e.g., exclude test environments).
Filters help you focus your metric on relevant data and remove noise.
9
Time Period
Select the window of data to include in the metric (e.g., Last 30 days, Last 12 months).
This controls how much historical data is shown to your customers in dashboards.
Once your metric is created, you can immediately start sending events and see your events in the Quivly events dashboard.