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stage	group	info
Analytics	Product Intelligence	To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments

Metrics instrumentation guide

This guide describes how to develop Service Ping metrics using metrics instrumentation.

For a video tutorial, see the Adding Service Ping metric via instrumentation class.

Nomenclature

Instrumentation class:
- Inherits one of the metric classes: DatabaseMetric, RedisMetric, RedisHLLMetric, NumbersMetric 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 field, which can be set to a class.

The defined instrumentation class should inherit one of the existing metric classes: DatabaseMetric, RedisMetric, RedisHLLMetric, NumbersMetric or GenericMetric.

The current convention is that a single instrumentation class corresponds to a single metric. On rare occasions, there are exceptions to that convention like Redis metrics. To use a single instrumentation class for more than one metric, please reach out to one of the @gitlab-org/analytics-section/product-intelligence/engineers members to consult about your case.

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

operation: Operations for the given relation, one of count, distinct_count, sum, and average.
relation: ActiveRecord::Relation for the objects we want to perform the operation.
start: Specifies the start value of the batch counting, by default is relation.minimum(:id).
finish: Specifies the end value of the batch counting, by default is relation.maximum(:id).
cache_start_and_finish_as: Specifies the cache key for start and finish values and sets up caching them. Use this call when start and finish are expensive queries that should be reused between different metric calculations.
available?: Specifies whether the metric should be reported. The default is true.
timestamp_column: Optionally specifies timestamp column for metric used to filter records for time constrained metrics. The default is created_at.

Example of a merge request that adds a database metric.

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class CountBoardsMetric < DatabaseMetric
          operation :count

          relation { Board }
        end
      end
    end
  end
end

Ordinary batch counters Example

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class CountIssuesMetric < DatabaseMetric
          operation :count

          start { Issue.minimum(:id) }
          finish { Issue.maximum(:id) }

          relation { Issue }
        end
      end
    end
  end
end

Distinct batch counters Example

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class CountUsersAssociatingMilestonesToReleasesMetric < DatabaseMetric
          operation :distinct_count, column: :author_id

          relation { Release.with_milestones }

          start { Release.minimum(:author_id) }
          finish { Release.maximum(:author_id) }
        end
      end
    end
  end
end

Sum Example

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class JiraImportsTotalImportedIssuesCountMetric < DatabaseMetric
          operation :sum, column: :imported_issues_count

          relation { JiraImportState.finished }
        end
      end
    end
  end
end

Average Example

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class CountIssuesWeightAverageMetric < DatabaseMetric
          operation :average, column: :weight

          relation { Issue }
        end
      end
    end
  end
end

Redis metrics

Example of a merge request that adds a Redis metric.

Count unique values for source_code_pushes event.

Required options:

event: the event name.
counter_class: one of the counter classes from the Gitlab::UsageDataCounters namespace; it should implement read method or inherit it from BaseCounter.

time_frame: all
data_source: redis
instrumentation_class: 'RedisMetric'
options:
  event: pushes
  counter_class: SourceCodeCounter

Availability-restrained Redis metrics

If the Redis metric should only be available in the report under some conditions, then you must specify these conditions in a new class that is a child of the RedisMetric class.

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class MergeUsageCountRedisMetric < RedisMetric
          available? { Feature.enabled?(:merge_usage_data_missing_key_paths) }
        end
      end
    end
  end
end

You must also use the class's name in the YAML setup.

time_frame: all
data_source: redis
instrumentation_class: 'MergeUsageCountRedisMetric'
options:
  event: pushes
  counter_class: SourceCodeCounter

Redis HyperLogLog metrics

Example of a merge request that adds a RedisHLL metric.

Count unique values for i_quickactions_approve event.

time_frame: 28d
data_source: redis_hll
instrumentation_class: 'RedisHLLMetric'
options:
  events:
    - i_quickactions_approve

Availability-restrained Redis HyperLogLog metrics

If the Redis HyperLogLog metric should only be available in the report under some conditions, then you must specify these conditions in a new class that is a child of the RedisHLLMetric class.

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class MergeUsageCountRedisHLLMetric < RedisHLLMetric
          available? { Feature.enabled?(:merge_usage_data_missing_key_paths) }
        end
      end
    end
  end
end

You must also use the class's name in the YAML setup.

time_frame: 28d
data_source: redis_hll
instrumentation_class: 'MergeUsageCountRedisHLLMetric'
options:
  events:
    - i_quickactions_approve

Numbers metrics

operation: Operations for the given data block. Currently we only support add operation.
data: a block which contains an array of numbers.
available?: Specifies whether the metric should be reported. The default is true.

# frozen_string_literal: true

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
          class IssuesBoardsCountMetric < NumbersMetric
            operation :add

            data do |time_frame|
              [
                 CountIssuesMetric.new(time_frame: time_frame).value,
                 CountBoardsMetric.new(time_frame: time_frame).value
              ]
            end
          end
        end
      end
    end
  end
end

You must also include the instrumentation class name in the YAML setup.

time_frame: 28d
instrumentation_class: 'IssuesBoardsCountMetric'

Generic metrics

value: Specifies the value of the metric.
available?: Specifies whether the metric should be reported. The default is true.

Example of a merge request that adds a generic metric.

module Gitlab
  module Usage
    module Metrics
      module Instrumentations
        class UuidMetric < GenericMetric
          value do
            Gitlab::CurrentSettings.uuid
          end
        end
      end
    end
  end
end

Support for instrumentation classes

There is support for:

count, distinct_count, estimate_batch_distinct_count, sum, and average for database metrics.
Redis metrics.
Redis HLL metrics.
add for numbers metrics.
Generic metrics, which are metrics based on settings or configurations.

There is no support for:

add, histogram for database metrics.

You can track the progress to support these.

Create a new metric instrumentation class

To create a stub instrumentation for a Service Ping metric, you can use a dedicated generator:

The generator takes the class name as an argument and the following options:

--type=TYPE Required. Indicates the metric type. It must be one of: database, generic, redis, numbers.
--operation Required for database & numebers type.
- For database it must be one of: count, distinct_count, estimate_batch_distinct_count, sum, average.
- For numbers it must be: add.
--ee Indicates if the metric is for EE.

rails generate gitlab:usage_metric CountIssues --type database
        create lib/gitlab/usage/metrics/instrumentations/count_issues_metric.rb
        create spec/lib/gitlab/usage/metrics/instrumentations/count_issues_metric_spec.rb

Migrate Service Ping metrics to instrumentation classes

This guide describes how to migrate a Service Ping metric from lib/gitlab/usage_data.rb or ee/lib/ee/gitlab/usage_data.rb to instrumentation classes.

Choose the metric type:

Database metric
Redis HyperLogLog metrics
Redis metric
Numbers metric
Generic metric

Determine the location of instrumentation class: either under ee or outside ee.
Generate the instrumentation class file.
Fill the instrumentation class body:
- Add code logic for the metric. This might be similar to the metric implementation in usage_data.rb.
- Add tests for the individual metric spec/lib/gitlab/usage/metrics/instrumentations/.
- Add tests for Service Ping.
Generate the metric definition file.
Remove the code from lib/gitlab/usage_data.rb or ee/lib/ee/gitlab/usage_data.rb.
Remove the tests from spec/lib/gitlab/usage_data.rb or ee/spec/lib/ee/gitlab/usage_data.rb.

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