debian-mirror-gitlab/doc/development/telemetry/usage_ping.md

stage	group	info
Growth	Telemetry	To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#designated-technical-writers

Usage Ping Guide

• Introduced in GitLab Enterprise Edition 8.10.
• More statistics were added in GitLab Enterprise Edition 8.12.
• Moved to GitLab Core in 9.1.
• More statistics were added in GitLab Ultimate 11.2.

This guide describes Usage Ping's purpose and how it's implemented.

For more information about Telemetry, see:

• Telemetry Guide
• Snowplow Guide

More useful links:

• Telemetry Direction
• Data Analysis Process
• Data for Product Managers
• Data Infrastructure

What is Usage Ping?

• GitLab sends a weekly payload containing usage data to GitLab Inc. Usage Ping provides high-level data to help our product, support, and sales teams. It does not send any project names, usernames, or any other specific data. The information from the usage ping is not anonymous, it is linked to the hostname of the instance. Sending usage ping is optional, and any instance can disable analytics.
• The usage data is primarily composed of row counts for different tables in the instance’s database. By comparing these counts month over month (or week over week), we can get a rough sense for how an instance is using the different features within the product. In addition to counts, other facts that help us classify and understand GitLab installations are collected.
• Usage ping is important to GitLab as we use it to calculate our Stage Monthly Active Users (SMAU) which helps us measure the success of our stages and features.
• Once usage ping is enabled, GitLab will gather data from the other instances and will be able to show usage statistics of your instance to your users.

Why should we enable Usage Ping?

• The main purpose of Usage Ping is to build a better GitLab. Data about how GitLab is used is collected to better understand feature/stage adoption and usage, which helps us understand how GitLab is adding value and helps our team better understand the reasons why people use GitLab and with this knowledge we're able to make better product decisions.
• As a benefit of having the usage ping active, GitLab lets you analyze the users’ activities over time of your GitLab installation.
• As a benefit of having the usage ping active, GitLab provides you with The DevOps Score,which gives you an overview of your entire instance’s adoption of Concurrent DevOps from planning to monitoring.
• You will get better, more proactive support. (assuming that our TAMs and support organization used the data to deliver more value)
• You will get insight and advice into how to get the most value out of your investment in GitLab. Wouldn't you want to know that a number of features or values are not being adopted in your organization?
• You get a report that illustrates how you compare against other similar organizations (anonymized), with specific advice and recommendations on how to improve your DevOps processes.
• Usage Ping is enabled by default. To disable it, see Disable Usage Ping.

Limitations

• Usage Ping does not track frontend events things like page views, link clicks, or user sessions, and only focuses on aggregated backend events.
• Because of these limitations we recommend instrumenting your products with Snowplow for more detailed analytics on GitLab.com and use Usage Ping to track aggregated backend events on self-managed.

Usage Ping payload

You can view the exact JSON payload sent to GitLab Inc. in the administration panel. To view the payload:

1. Navigate to Admin Area > Settings > Metrics and profiling.
2. Expand the Usage statistics section.
3. Click the Preview payload button.

For an example payload, see Example Usage Ping payload.

Disable Usage Ping

To disable Usage Ping in the GitLab UI, go to the Settings page of your administration panel and uncheck the Usage Ping checkbox.

To disable Usage Ping and prevent it from being configured in the future through the administration panel, Omnibus installs can set the following in gitlab.rb:

gitlab_rails['usage_ping_enabled'] = false

Source installations can set the following in gitlab.yml:

production: &base
  # ...
  gitlab:
    # ...
    usage_ping_enabled: false

Usage Ping request flow

The following example shows a basic request/response flow between a GitLab instance, the Versions Application, the License Application, Salesforce, GitLab's S3 Bucket, GitLab's Snowflake Data Warehouse, and Sisense:

sequenceDiagram
    participant GitLab Instance
    participant Versions Application
    participant Licenses Application
    participant Salesforce
    participant S3 Bucket
    participant Snowflake DW
    participant Sisense Dashboards
    GitLab Instance->>Versions Application: Send Usage Ping
    loop Process usage data
        Versions Application->>Versions Application: Parse usage data
        Versions Application->>Versions Application: Write to database
        Versions Application->>Versions Application: Update license ping time
    end
    loop Process data for Salesforce
        Versions Application-xLicenses Application: Request Zuora subscription id
        Licenses Application-xVersions Application: Zuora subscription id
        Versions Application-xSalesforce: Request Zuora account id  by Zuora subscription id
        Salesforce-xVersions Application: Zuora account id
        Versions Application-xSalesforce: Usage data for the Zuora account
    end
    Versions Application->>S3 Bucket: Export Versions database
    S3 Bucket->>Snowflake DW: Import data
    Snowflake DW->>Snowflake DW: Transform data using dbt
    Snowflake DW->>Sisense Dashboards: Data available for querying
    Versions Application->>GitLab Instance: DevOps Score (Conversational Development Index)

How Usage Ping works

1. The Usage Ping cron job is set in Sidekiq to run weekly.
2. When the cron job runs, it calls GitLab::UsageData.to_json.
3. GitLab::UsageData.to_json cascades down to ~400+ other counter method calls.
4. The response of all methods calls are merged together into a single JSON payload in GitLab::UsageData.to_json.
5. The JSON payload is then posted to the Versions application.

Implementing Usage Ping

Usage Ping consists of two kinds of data, counters and observations. Counters track how often a certain event happened over time, such as how many CI pipelines have run. They are monotonic and always trend up. Observations are facts collected from one or more GitLab instances and can carry arbitrary data. There are no general guidelines around how to collect those, due to the individual nature of that data.

There are four types of counters which are all found in usage_data.rb:

• Ordinary Batch Counters: Simple count of a given ActiveRecord_Relation
• Distinct Batch Counters: Distinct count of a given ActiveRecord_Relation on given column
• Alternative Counters: Used for settings and configurations
• Redis Counters: Used for in-memory counts. This method is being deprecated due to data inaccuracies and will be replaced with a persistent method.

NOTE: Note: Only use the provided counter methods. Each counter method contains a built in fail safe to isolate each counter to avoid breaking the entire Usage Ping.

Why batch counting

For large tables, PostgreSQL can take a long time to count rows due to MVCC (Multi-version Concurrency Control). Batch counting is a counting method where a single large query is broken into multiple smaller queries. For example, instead of a single query querying 1,000,000 records, with batch counting, you can execute 100 queries of 10,000 records each. Batch counting is useful for avoiding database timeouts as each batch query is significantly shorter than one single long running query.

For GitLab.com, there are extremely large tables with 15 second query timeouts, so we use batch counting to avoid encountering timeouts. Here are the sizes of some GitLab.com tables:

Table	Row counts in millions
merge_request_diff_commits	2280
ci_build_trace_sections	1764
merge_request_diff_files	1082
events	514

There are two batch counting methods provided, Ordinary Batch Counters and Distinct Batch Counters. Batch counting requires indexes on columns to calculate max, min, and range queries. In some cases, a specialized index may need to be added on the columns involved in a counter.

Ordinary Batch Counters

Handles ActiveRecord::StatementInvalid error

Simple count of a given ActiveRecord_Relation

Method: count(relation, column = nil, batch: true, start: nil, finish: nil)

Arguments:

• relation the ActiveRecord_Relation to perform the count
• column the column to perform the count on, by default is the primary key
• batch: default true in order to use batch counting
• start: custom start of the batch counting in order to avoid complex min calculations
• end: custom end of the batch counting in order to avoid complex min calculations

Examples:

count(User.active)
count(::Clusters::Cluster.aws_installed.enabled, :cluster_id)
count(::Clusters::Cluster.aws_installed.enabled, :cluster_id, start: ::Clusters::Cluster.minimum(:id), finish: ::Clusters::Cluster.maximum(:id))

Distinct Batch Counters

Handles ActiveRecord::StatementInvalid error

Distinct count of a given ActiveRecord_Relation on given column

Method: distinct_count(relation, column = nil, batch: true, start: nil, finish: nil)

Arguments:

• relation the ActiveRecord_Relation to perform the count
• column the column to perform the distinct count, by default is the primary key
• batch: default true in order to use batch counting
• start: custom start of the batch counting in order to avoid complex min calculations
• end: custom end of the batch counting in order to avoid complex min calculations

Examples:

distinct_count(::Project, :creator_id)
distinct_count(::Note.with_suggestions.where(time_period), :author_id, start: ::User.minimum(:id), finish: ::User.maximum(:id))
distinct_count(::Clusters::Applications::CertManager.where(time_period).available.joins(:cluster), 'clusters.user_id')

Redis Counters

Handles ::Redis::CommandError and Gitlab::UsageDataCounters::BaseCounter::UnknownEvent returns -1 when a block is sent or hash with all values -1 when a counter(Gitlab::UsageDataCounters) is sent different behavior due to 2 different implementations of Redis counter

Method: redis_usage_data(counter, &block)

Arguments:

• counter: a counter from Gitlab::UsageDataCounters, that has fallback_totals method implemented
• or a block: which is evaluated

Example of usage:

redis_usage_data(Gitlab::UsageDataCounters::WikiPageCounter)
redis_usage_data { ::Gitlab::UsageCounters::PodLogs.usage_totals[:total] }

Note that Redis counters are in the process of being deprecated and you should instead try to use Snowplow events instead. We're in the process of building self-managed event tracking and once this is available, we will convert all Redis counters into Snowplow events.

Alternative Counters

Handles StandardError and fallbacks into -1 this way not all measures fail if we encounter one exception. Mainly used for settings and configurations.

Method: alt_usage_data(value = nil, fallback: -1, &block)

Arguments:

• value: a simple static value in which case the value is simply returned.
• or a block: which is evaluated
• fallback: -1: the common value used for any metrics that are failing.

Example of usage:

alt_usage_data { Gitlab::VERSION }
alt_usage_data { Gitlab::CurrentSettings.uuid }
alt_usage_data(999)

Prometheus Queries

In those cases where operational metrics should be part of Usage Ping, a database or Redis query is unlikely to provide useful data. Instead, Prometheus might be more appropriate, since most of GitLab's architectural components publish metrics to it that can be queried back, aggregated, and included as usage data.

NOTE: Note: Prometheus as a data source for Usage Ping is currently only available for single-node Omnibus installations that are running the bundled Prometheus instance.

In order to query Prometheus for metrics, a helper method is available that will yield a fully configured PrometheusClient, given it is available as per the note above:

with_prometheus_client do |client|
  response = client.query('<your query>')
  ...
end

Please refer to the PrometheusClient definition for how to use its API to query for data.

Developing and testing Usage Ping

1. Use your Rails console to manually test counters

# count
Gitlab::UsageData.count(User.active)
Gitlab::UsageData.count(::Clusters::Cluster.aws_installed.enabled, :cluster_id)

# count distinct
Gitlab::UsageData.distinct_count(::Project, :creator_id)
Gitlab::UsageData.distinct_count(::Note.with_suggestions.where(time_period), :author_id, start: ::User.minimum(:id), finish: ::User.maximum(:id))

2. Generate the SQL query

Your Rails console will return the generated SQL queries.

Example:

pry(main)> Gitlab::UsageData.count(User.active)
   (2.6ms)  SELECT "features"."key" FROM "features"
   (15.3ms)  SELECT MIN("users"."id") FROM "users" WHERE ("users"."state" IN ('active')) AND ("users"."user_type" IS NULL OR "users"."user_type" IN (6, 4))
   (2.4ms)  SELECT MAX("users"."id") FROM "users" WHERE ("users"."state" IN ('active')) AND ("users"."user_type" IS NULL OR "users"."user_type" IN (6, 4))
   (1.9ms)  SELECT COUNT("users"."id") FROM "users" WHERE ("users"."state" IN ('active')) AND ("users"."user_type" IS NULL OR "users"."user_type" IN (6, 4)) AND "users"."id" BETWEEN 1 AND 100000

3. Optimize queries with #database-lab

Paste the SQL query into #database-lab to see how the query performs at scale.

• #database-lab is a Slack channel which uses a production-sized environment to test your queries.
• GitLab.com’s production database has a 15 second timeout.
• For each query we require an execution time of under 1 second due to cold caches which can 10x this time.
• Add a specialized index on columns involved to reduce the execution time.

In order to have an understanding of the query's execution we add in the MR description the following information:

• For counters that have a time_period test we add information for both cases:
  • time_period = {} for all time periods
  • time_period = { created_at: 28.days.ago..Time.current } for last 28 days period
• Execution plan and query time before and after optimization
• Query generated for the index and time
• Migration output for up and down execution

We also use #database-lab and explain.depesz.com. For more details, see the database review guide.

Examples of query optimization work:

• Example 1
• Example 2

4. Add the metric definition

When adding, changing, or updating metrics, please update the Usage Statistics definition table.

5. Add new metric to Versions Application

Check if new metrics need to be added to the Versions Application. See usage_data schema and usage data parameters accepted. Any metrics added under the counts key are saved in the counts column.

6. Ask for a Telemetry Review

On GitLab.com, we have DangerBot setup to monitor Telemetry related files and DangerBot will recommend a Telemetry review. Mention @gitlab-org/growth/telemetry/engineers in your MR for a review.

Optional: Test Prometheus based Usage Ping

If the data submitted includes metrics queried from Prometheus that you would like to inspect and verify, then you need to ensure that a Prometheus server is running locally, and that furthermore the respective GitLab components are exporting metrics to it. If you do not need to test data coming from Prometheus, no further action is necessary, since Usage Ping should degrade gracefully in the absence of a running Prometheus server.

There are currently three kinds of components that may export data to Prometheus, and which are included in Usage Ping:

• node_exporter - Exports node metrics from the host machine
• gitlab-exporter - Exports process metrics from various GitLab components
• various GitLab services such as Sidekiq and the Rails server that export their own metrics

Test with an Omnibus container

This is the recommended approach to test Prometheus based Usage Ping.

The easiest way to verify your changes is to build a new Omnibus image from your code branch via CI, then download the image and run a local container instance:

1. From your merge request, click on the qa stage, then trigger the package-and-qa job. This job will trigger an Omnibus build in a downstream pipeline of the omnibus-gitlab-mirror project.
2. In the downstream pipeline, wait for the gitlab-docker job to finish.
3. Open the job logs and locate the full container name including the version. It will take the following form: registry.gitlab.com/gitlab-org/build/omnibus-gitlab-mirror/gitlab-ee:<VERSION>.
4. On your local machine, make sure you are logged in to the GitLab Docker registry. You can find the instructions for this in Authenticating to the GitLab Container Registry.
5. Once logged in, download the new image via docker pull registry.gitlab.com/gitlab-org/build/omnibus-gitlab-mirror/gitlab-ee:<VERSION>
6. For more information about working with and running Omnibus GitLab containers in Docker, please refer to GitLab Docker images in the Omnibus documentation.

Test with GitLab development toolkits

This is the less recommended approach, since it comes with a number of difficulties when emulating a real GitLab deployment.

The GDK is not currently set up to run a Prometheus server or node_exporter alongside other GitLab components. If you would like to do so, Monitoring the GDK with Prometheus is a good start.

The GCK has limited support for testing Prometheus based Usage Ping. By default, it already comes with a fully configured Prometheus service that is set up to scrape a number of components, but with the following limitations:

• It does not currently run a gitlab-exporter instance, so several process_* metrics from services such as Gitaly may be missing.
• While it runs a node_exporter, docker-compose services emulate hosts, meaning that it would normally report itself to not be associated with any of the other services that are running. That is not how node metrics are reported in a production setup, where node_exporter always runs as a process alongside other GitLab components on any given node. From Usage Ping's perspective none of the node data would therefore appear to be associated to any of the services running, since they all appear to be running on different hosts. To alleviate this problem, the node_exporter in GCK was arbitrarily "assigned" to the web service, meaning only for this service node_* metrics will appear in Usage Ping.

Usage Statistics definitions

Statistic	Section	Stage	Tier	Description
uuid
hostname
version
installation_type
active_user_count
recorded_at
edition
license_md5
license_id
historical_max_users
Name	licensee
Email	licensee
Company	licensee
license_user_count
license_starts_at
license_expires_at
license_plan
license_trial
assignee_lists	counts
boards	counts
ci_builds	counts	verify		Unique builds in project
ci_internal_pipelines	counts	verify		Total pipelines in GitLab repositories
ci_external_pipelines	counts	verify		Total pipelines in external repositories
ci_pipeline_config_auto_devops	counts	verify		Total pipelines from an Auto DevOps template
ci_pipeline_config_repository	counts	verify		Total Pipelines from templates in repository
ci_runners	counts	verify		Total configured Runners in project
ci_triggers	counts	verify		Total configured Triggers in project
ci_pipeline_schedules	counts	verify		Pipeline schedules in GitLab
auto_devops_enabled	counts	configure		Projects with Auto DevOps template enabled
auto_devops_disabled	counts	configure		Projects with Auto DevOps template disabled
deploy_keys	counts
deployments	counts	release		Total deployments
dast_jobs	counts
successful_deployments	counts	release		Total successful deployments
failed_deployments	counts	release		Total failed deployments
environments	counts	release		Total available and stopped environments
clusters	counts	configure		Total GitLab Managed clusters both enabled and disabled
clusters_enabled	counts	configure		Total GitLab Managed clusters currently enabled
project_clusters_enabled	counts	configure		Total GitLab Managed clusters attached to projects
group_clusters_enabled	counts	configure		Total GitLab Managed clusters attached to groups
instance_clusters_enabled	counts	configure		Total GitLab Managed clusters attached to the instance
clusters_disabled	counts	configure		Total GitLab Managed disabled clusters
project_clusters_disabled	counts	configure		Total GitLab Managed disabled clusters previously attached to projects
group_clusters_disabled	counts	configure		Total GitLab Managed disabled clusters previously attached to groups
instance_clusters_disabled	counts	configure		Total GitLab Managed disabled clusters previously attached to the instance
clusters_platforms_eks	counts	configure		Total GitLab Managed clusters provisioned with GitLab on AWS EKS
clusters_platforms_gke	counts	configure		Total GitLab Managed clusters provisioned with GitLab on GCE GKE
clusters_platforms_user	counts	configure		Total GitLab Managed clusters that are user provisioned
clusters_applications_helm	counts	configure		Total GitLab Managed clusters with Helm enabled
clusters_applications_ingress	counts	configure		Total GitLab Managed clusters with Ingress enabled
clusters_applications_cert_managers	counts	configure		Total GitLab Managed clusters with Cert Manager enabled
clusters_applications_crossplane	counts	configure		Total GitLab Managed clusters with Crossplane enabled
clusters_applications_prometheus	counts	configure		Total GitLab Managed clusters with Prometheus enabled
clusters_applications_runner	counts	configure		Total GitLab Managed clusters with Runner enabled
clusters_applications_knative	counts	configure		Total GitLab Managed clusters with Knative enabled
clusters_applications_elastic_stack	counts	configure		Total GitLab Managed clusters with Elastic Stack enabled
clusters_management_project	counts	configure		Total GitLab Managed clusters with defined cluster management project
in_review_folder	counts
grafana_integrated_projects	counts
groups	counts
issues	counts
issues_created_from_gitlab_error_tracking_ui	counts	monitor
issues_with_associated_zoom_link	counts	monitor
issues_using_zoom_quick_actions	counts	monitor
issues_with_embedded_grafana_charts_approx	counts	monitor
issues_with_health_status	counts
keys	counts
label_lists	counts
lfs_objects	counts
milestone_lists	counts
milestones	counts
pages_domains	counts	release		Total GitLab Pages domains
pool_repositories	counts
projects	counts
projects_imported_from_github	counts
projects_with_repositories_enabled	counts
projects_with_error_tracking_enabled	counts	monitor
protected_branches	counts
releases	counts	release		Unique release tags
remote_mirrors	counts
requirements_created	counts
snippets	counts
suggestions	counts
todos	counts
uploads	counts
web_hooks	counts
projects_alerts_active	counts
projects_asana_active	counts
projects_assembla_active	counts
projects_bamboo_active	counts
projects_bugzilla_active	counts
projects_buildkite_active	counts
projects_campfire_active	counts
projects_custom_issue_tracker_active	counts
projects_discord_active	counts
projects_drone_ci_active	counts
projects_emails_on_push_active	counts
projects_external_wiki_active	counts
projects_flowdock_active	counts
projects_github_active	counts
projects_hangouts_chat_active	counts
projects_hipchat_active	counts
projects_irker_active	counts
projects_jenkins_active	counts
projects_jira_active	counts
projects_mattermost_active	counts
projects_mattermost_slash_commands_active	counts
projects_microsoft_teams_active	counts
projects_packagist_active	counts
projects_pipelines_email_active	counts
projects_pivotaltracker_active	counts
projects_prometheus_active	counts
projects_pushover_active	counts
projects_redmine_active	counts
projects_slack_active	counts
projects_slack_slash_commands_active	counts
projects_teamcity_active	counts
projects_unify_circuit_active	counts
projects_webex_teams_active	counts
projects_youtrack_active	counts
projects_slack_notifications_active	counts
projects_slack_slash_active	counts
projects_jira_server_active	counts
projects_jira_cloud_active	counts
projects_jira_dvcs_cloud_active	counts
projects_jira_dvcs_server_active	counts
labels	counts
merge_requests	counts
merge_requests_users	counts
notes	counts
wiki_pages_create	counts
wiki_pages_update	counts
wiki_pages_delete	counts
web_ide_commits	counts
web_ide_views	counts
web_ide_merge_requests	counts
web_ide_previews	counts
snippet_comment	counts
commit_comment	counts
merge_request_comment	counts
snippet_create	counts
snippet_update	counts
navbar_searches	counts
cycle_analytics_views	counts
productivity_analytics_views	counts
source_code_pushes	counts
merge_request_create	counts
design_management_designs_create	counts
design_management_designs_update	counts
design_management_designs_delete	counts
licenses_list_views	counts
user_preferences_group_overview_details	counts
user_preferences_group_overview_security_dashboard	counts
ingress_modsecurity_logging	counts
ingress_modsecurity_blocking	counts
ingress_modsecurity_disabled	counts
ingress_modsecurity_not_installed	counts
dependency_list_usages_total	counts
epics	counts
feature_flags	counts
geo_nodes	counts	geo		Number of sites in a Geo deployment
geo_event_log_max_id	counts	geo		Number of replication events on a Geo primary
incident_issues	counts	monitor		Issues created by the alert bot
alert_bot_incident_issues	counts	monitor		Issues created by the alert bot
incident_labeled_issues	counts	monitor		Issues with the incident label
issues_created_gitlab_alerts	counts	monitor		Issues created from alerts by non-alert bot users
issues_created_manually_from_alerts	counts	monitor		Issues created from alerts by non-alert bot users
issues_created_from_alerts	counts	monitor		Issues created from Prometheus and alert management alerts
ldap_group_links	counts
ldap_keys	counts
ldap_users	counts
pod_logs_usages_total	counts
projects_enforcing_code_owner_approval	counts
projects_mirrored_with_pipelines_enabled	counts	release		Projects with repository mirroring enabled
projects_reporting_ci_cd_back_to_github	counts	verify		Projects with a GitHub service pipeline enabled
projects_with_packages	counts	package		Projects with package registry configured
projects_with_prometheus_alerts	counts	monitor		Projects with Prometheus alerting enabled
projects_with_tracing_enabled	counts	monitor		Projects with tracing enabled
projects_with_alerts_service_enabled	counts	monitor		Projects with alerting service enabled
template_repositories	counts
container_scanning_jobs	counts
dependency_scanning_jobs	counts
license_management_jobs	counts
sast_jobs	counts
status_page_projects	counts	monitor		Projects with status page enabled
status_page_issues	counts	monitor		Issues published to a Status Page
status_page_incident_publishes	counts	monitor		Cumulative count of usages of publish operation
status_page_incident_unpublishes	counts	monitor		Cumulative count of usages of unpublish operation
epics_deepest_relationship_level	counts
operations_dashboard_default_dashboard	counts	monitor		Active users with enabled operations dashboard
operations_dashboard_users_with_projects_added	counts	monitor		Active users with projects on operations dashboard
container_registry_enabled
dependency_proxy_enabled
gitlab_shared_runners_enabled
gravatar_enabled
ldap_enabled
mattermost_enabled
omniauth_enabled
prometheus_metrics_enabled
reply_by_email_enabled
average	avg_cycle_analytics - code
sd	avg_cycle_analytics - code
missing	avg_cycle_analytics - code
average	avg_cycle_analytics - test
sd	avg_cycle_analytics - test
missing	avg_cycle_analytics - test
average	avg_cycle_analytics - review
sd	avg_cycle_analytics - review
missing	avg_cycle_analytics - review
average	avg_cycle_analytics - staging
sd	avg_cycle_analytics - staging
missing	avg_cycle_analytics - staging
average	avg_cycle_analytics - production
sd	avg_cycle_analytics - production
missing	avg_cycle_analytics - production
total	avg_cycle_analytics
clusters_applications_cert_managers	usage_activity_by_stage	configure		Unique clusters with certificate managers enabled
clusters_applications_helm	usage_activity_by_stage	configure		Unique clusters with Helm enabled
clusters_applications_ingress	usage_activity_by_stage	configure		Unique clusters with Ingress enabled
clusters_applications_knative	usage_activity_by_stage	configure		Unique clusters with Knative enabled
clusters_management_project	usage_activity_by_stage	configure		Unique clusters with project management enabled
clusters_disabled	usage_activity_by_stage	configure		Total non-"GitLab Managed clusters"
clusters_enabled	usage_activity_by_stage	configure		Total GitLab Managed clusters
clusters_platforms_gke	usage_activity_by_stage	configure		Unique clusters with Google Cloud installed
clusters_platforms_eks	usage_activity_by_stage	configure		Unique clusters with AWS installed
clusters_platforms_user	usage_activity_by_stage	configure		Unique clusters that are user provided
instance_clusters_disabled	usage_activity_by_stage	configure		Unique clusters disabled on instance
instance_clusters_enabled	usage_activity_by_stage	configure		Unique clusters enabled on instance
group_clusters_disabled	usage_activity_by_stage	configure		Unique clusters disabled on group
group_clusters_enabled	usage_activity_by_stage	configure		Unique clusters enabled on group
project_clusters_disabled	usage_activity_by_stage	configure		Unique clusters disabled on project
project_clusters_enabled	usage_activity_by_stage	configure		Unique clusters enabled on project
projects_slack_notifications_active	usage_activity_by_stage	configure		Unique projects with Slack service enabled
projects_slack_slash_active	usage_activity_by_stage	configure		Unique projects with Slack '/' commands enabled
projects_with_prometheus_alerts: 0	usage_activity_by_stage	monitor		Projects with Prometheus enabled and no alerts
deploy_keys	usage_activity_by_stage	create
keys	usage_activity_by_stage	create
projects_jira_dvcs_server_active	usage_activity_by_stage	plan
service_desk_enabled_projects	usage_activity_by_stage	plan
service_desk_issues	usage_activity_by_stage	plan
todos: 0	usage_activity_by_stage	plan
deployments	usage_activity_by_stage	release		Total deployments
failed_deployments	usage_activity_by_stage	release		Total failed deployments
projects_mirrored_with_pipelines_enabled	usage_activity_by_stage	release		Projects with repository mirroring enabled
releases	usage_activity_by_stage	release		Unique release tags in project
successful_deployments: 0	usage_activity_by_stage	release		Total successful deployments
user_preferences_group_overview_security_dashboard: 0	usage_activity_by_stage	secure
ci_builds	usage_activity_by_stage	verify		Unique builds in project
ci_external_pipelines	usage_activity_by_stage	verify		Total pipelines in external repositories
ci_internal_pipelines	usage_activity_by_stage	verify		Total pipelines in GitLab repositories
ci_pipeline_config_auto_devops	usage_activity_by_stage	verify		Total pipelines from an Auto DevOps template
ci_pipeline_config_repository	usage_activity_by_stage	verify		Pipelines from templates in repository
ci_pipeline_schedules	usage_activity_by_stage	verify		Pipeline schedules in GitLab
ci_pipelines	usage_activity_by_stage	verify		Total pipelines
ci_triggers	usage_activity_by_stage	verify		Triggers enabled
clusters_applications_runner	usage_activity_by_stage	verify		Unique clusters with Runner enabled
projects_reporting_ci_cd_back_to_github: 0	usage_activity_by_stage	verify		Unique projects with a GitHub pipeline enabled
nodes	topology	enablement		The list of server nodes on which GitLab components are running
duration_s	topology	enablement		Time it took to collect topology data
node_memory_total_bytes	topology > nodes	enablement		The total available memory of this node
node_cpus	topology > nodes	enablement		The number of CPU cores of this node
node_services	topology > nodes	enablement		The list of GitLab services running on this node
name	topology > nodes > node_services	enablement		The name of the GitLab service running on this node
process_count	topology > nodes > node_services	enablement		The number of processes running for this service
process_memory_rss	topology > nodes > node_services	enablement		The average Resident Set Size of a service process
process_memory_uss	topology > nodes > node_services	enablement		The average Unique Set Size of a service process
process_memory_pss	topology > nodes > node_services	enablement		The average Proportional Set Size of a service process

Example Usage Ping payload

The following is example content of the Usage Ping payload.

{
  "uuid": "0000000-0000-0000-0000-000000000000",
  "hostname": "example.com",
  "version": "12.10.0-pre",
  "installation_type": "omnibus-gitlab",
  "active_user_count": 999,
  "recorded_at": "2020-04-17T07:43:54.162+00:00",
  "edition": "EEU",
  "license_md5": "00000000000000000000000000000000",
  "license_id": null,
  "historical_max_users": 999,
  "licensee": {
    "Name": "ABC, Inc.",
    "Email": "email@example.com",
    "Company": "ABC, Inc."
  },
  "license_user_count": 999,
  "license_starts_at": "2020-01-01",
  "license_expires_at": "2021-01-01",
  "license_plan": "ultimate",
  "license_add_ons": {
  },
  "license_trial": false,
  "counts": {
    "assignee_lists": 999,
    "boards": 999,
    "ci_builds": 999,
    ...
  },
  "container_registry_enabled": true,
  "dependency_proxy_enabled": false,
  "gitlab_shared_runners_enabled": true,
  "gravatar_enabled": true,
  "influxdb_metrics_enabled": true,
  "ldap_enabled": false,
  "mattermost_enabled": false,
  "omniauth_enabled": true,
  "prometheus_metrics_enabled": false,
  "reply_by_email_enabled": "incoming+%{key}@incoming.gitlab.com",
  "signup_enabled": true,
  "web_ide_clientside_preview_enabled": true,
  "ingress_modsecurity_enabled": true,
  "projects_with_expiration_policy_disabled": 999,
  "projects_with_expiration_policy_enabled": 999,
  ...
  "elasticsearch_enabled": true,
  "license_trial_ends_on": null,
  "geo_enabled": false,
  "git": {
    "version": {
      "major": 2,
      "minor": 26,
      "patch": 1
    }
  },
  "gitaly": {
    "version": "12.10.0-rc1-93-g40980d40",
    "servers": 56,
    "clusters": 14,
    "filesystems": [
      "EXT_2_3_4"
    ]
  },
  "gitlab_pages": {
    "enabled": true,
    "version": "1.17.0"
  },
  "database": {
    "adapter": "postgresql",
    "version": "9.6.15"
  },
  "app_server": {
    "type": "console"
  },
  "avg_cycle_analytics": {
    "issue": {
      "average": 999,
      "sd": 999,
      "missing": 999
    },
    "plan": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "code": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "test": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "review": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "staging": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "production": {
      "average": null,
      "sd": 999,
      "missing": 999
    },
    "total": 999
  },
  "usage_activity_by_stage": {
    "configure": {
      "project_clusters_enabled": 999,
      ...
    },
    "create": {
      "merge_requests": 999,
      ...
    },
    "manage": {
      "events": 999,
      ...
    },
    "monitor": {
      "clusters": 999,
      ...
    },
    "package": {
      "projects_with_packages": 999
    },
    "plan": {
      "issues": 999,
      ...
    },
    "release": {
      "deployments": 999,
      ...
    },
    "secure": {
      "user_container_scanning_jobs": 999,
      ...
    },
    "verify": {
      "ci_builds": 999,
      ...
    }
  },
  "usage_activity_by_stage_monthly": {
    "configure": {
      "project_clusters_enabled": 999,
      ...
    },
    "create": {
      "merge_requests": 999,
      ...
    },
    "manage": {
      "events": 999,
      ...
    },
    "monitor": {
      "clusters": 999,
      ...
    },
    "package": {
      "projects_with_packages": 999
    },
    "plan": {
      "issues": 999,
      ...
    },
    "release": {
      "deployments": 999,
      ...
    },
    "secure": {
      "user_container_scanning_jobs": 999,
      ...
    },
    "verify": {
      "ci_builds": 999,
      ...
    }
  },
  "topology": {
    "nodes": [
      {
        "node_memory_total_bytes": 33269903360,
        "node_cpus": 16,
        "node_services": [
          {
            "name": "web",
            "process_count": 16,
            "process_memory_pss": 233349888,
            "process_memory_rss": 788220927,
            "process_memory_uss": 195295487
          },
          {
            "name": "sidekiq",
            "process_count": 1,
            "process_memory_pss": 734080000,
            "process_memory_rss": 750051328,
            "process_memory_uss": 731533312
          },
          ...
        ],
        ...
      },
      ...
    ],
    "duration_s": 0.013836685999194742
  }
}