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# Metrics instrumentation guide
This guide describes how to develop Service Ping metrics using metrics instrumentation.
## Nomenclature
- **Instrumentation class**:
- Inherits one of the metric classes: `DatabaseMetric`, `RedisHLLMetric` or `GenericMetric`.
- Implements the logic that calculates the value for a Service Ping metric.
- **Metric definition**
The Service Data metric YAML definition.
- **Hardening**:
Hardening a method is the process that ensures the method fails safe, returning a fallback value like -1.
## How it works
A metric definition has the [`instrumentation_class`](metrics_dictionary.md) field, which can be set to a class.
The defined instrumentation class should have one of the existing metric classes: `DatabaseMetric`, `RedisHLLMetric`, or `GenericMetric`.
Using the instrumentation classes ensures that metrics can fail safe individually, without breaking the entire
process of Service Ping generation.
We have built a domain-specific language (DSL) to define the metrics instrumentation.
## Database metrics
[Example of a merge request that adds a database metric](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/60022).
```ruby
module Gitlab
module Usage
module Metrics
module Instrumentations
class CountBoardsMetric <DatabaseMetric
operation :count
relation { Board }
end
end
end
end
end
```
## Redis HyperLogLog metrics
[Example of a merge request that adds a `RedisHLL` metric](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/61685).
Count unique values for `i_quickactions_approve` event.
To create a stub instrumentation for a Service Ping metric, you can use a dedicated [generator](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/generators/gitlab/usage_metric_generator.rb):
The generator takes the class name as an argument and the following options: