Service Ping Guide (FREE SELF)

Introduced in GitLab Ultimate 11.2, more statistics.

In GitLab 14.1, renamed from Usage Ping to Service Ping. In 14.0 and earlier, use the Usage Ping documentation for the Rails commands appropriate to your version.

Service Ping is a GitLab process that collects and sends a weekly payload to GitLab. The payload provides important high-level data that helps our product, support, and sales teams understand how GitLab is used. The data helps to:

Compare counts month over month (or week over week) to get a rough sense for how an instance uses different product features.
Collect other facts that help us classify and understand GitLab installations.
Calculate our stage monthly active users (SMAU), which helps to measure the success of our stages and features.

Service Ping information is not anonymous. It's linked to the instance's hostname, but does not contain project names, usernames, or any other specific data.

Sending a Service Ping payload is optional and you can disable it on any self-managed instance. When Service Ping is enabled, GitLab gathers data from the other instances and can show your instance's usage statistics to your users.

Service Ping terminology

We use the following terminology to describe the Service Ping components:

Service Ping: the process that collects and generates a JSON payload.
Service Data: the contents of the Service Ping JSON payload. This includes metrics.
Metrics: primarily made up of row counts for different tables in an instance's database. Each metric has a corresponding metric definition in a YAML file.
MAU: monthly active users.
WAU: weekly active users.

Limitations

Service Ping does not track frontend events things like page views, link clicks, or user sessions.
Service Ping focuses only on aggregated backend events.

Because of these limitations we recommend you:

Instrument your products with Snowplow for more detailed analytics on GitLab.com.
Use Service Ping to track aggregated backend events on self-managed instances.

Service Ping request flow

The following example shows a basic request/response flow between a GitLab instance, the Versions Application, the License Application, Salesforce, the GitLab S3 Bucket, the GitLab 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 Service 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 Service Ping works

The Service Ping cron job is set in Sidekiq to run weekly.
When the cron job runs, it calls Gitlab::Usage::ServicePingReport.for(output: :all_metrics_values).
Gitlab::Usage::ServicePingReport.for(output: :all_metrics_values) cascades down to ~400+ other counter method calls.
The response of all methods calls are merged together into a single JSON payload.
The JSON payload is then posted to the Versions application If a firewall exception is needed, the required URL depends on several things. If the hostname is version.gitlab.com, the protocol is TCP, and the port number is 443, the required URL is https://version.gitlab.com/.
In case of an error, it will be reported to the Version application along with following pieces of information:
- uuid - GitLab instance unique identifier
- hostname - GitLab instance hostname
- version - GitLab instance current versions
- elapsed - Amount of time which passed since Service Ping report process started and moment of error occurrence
- message - Error message
```
 {
   "uuid"=>"02333324-1cd7-4c3b-a45b-a4993f05fb1d",
   "hostname"=>"127.0.0.1",
   "version"=>"14.7.0-pre",
   "elapsed"=>0.006946,
   "message"=>'PG::UndefinedColumn: ERROR:  column \"non_existent_attribute\" does not exist\nLINE 1: SELECT COUNT(non_existent_attribute) FROM \"issues\" /*applica...'
 }
 
```
Finally, the timing metadata information that is used for diagnostic purposes is submitted to the Versions application. It consists of a list of metric identifiers and the time it took to calculate the metrics:
- Introduced in GitLab 15.0 [with a flag(../../user/feature_flags.md), enabled by default.
- Generally available in GitLab 15.2. Feature flag measure_service_ping_metric_collection removed.

    { 
      "metadata"=>
      {
        "uuid"=>"0000000-0000-0000-0000-000000000000",
        "metrics"=>
        [{"name"=>"version", "time_elapsed"=>1.1811964213848114e-05},
         {"name"=>"installation_type", "time_elapsed"=>0.00017242692410945892},
         {"name"=>"license_billable_users", "time_elapsed"=>0.009520471096038818},
         ....
         {"name"=>"counts.clusters_platforms_eks",
          "time_elapsed"=>0.05638605775311589},
         {"name"=>"counts.clusters_platforms_gke",
          "time_elapsed"=>0.40995341585949063},
         {"name"=>"counts.clusters_platforms_user",
          "time_elapsed"=>0.06410990096628666},
         {"name"=>"counts.clusters_management_project",
          "time_elapsed"=>0.24020783510059118}
        ]
      }
    }
    ```

### On a Geo secondary site

We also collect metrics specific to [Geo](../../administration/geo/index.md) secondary sites to send with Service Ping.

1. The [Geo secondary service ping cron job](https://gitlab.com/gitlab-org/gitlab/-/blob/master/ee/app/workers/geo/secondary_usage_data_cron_worker.rb) is set in Sidekiq to run weekly.
1. When the cron job runs, it calls [`SecondaryUsageData.update_metrics!`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/ee/app/models/geo/secondary_usage_data.rb#L33). This collects the relevant metrics from Prometheus and stores the data in the Geo secondary tracking database for transmission to the primary site during a [Geo node status update](https://gitlab.com/gitlab-org/gitlab/-/blob/master/ee/app/models/geo_node_status.rb#L105).
1. Geo node status data is sent with the JSON payload in the process described above. The following is an example of the payload where each object in the array represents a Geo node:

   ```json
   [
     {
       "repository_verification_enabled"=>true,
       "repositories_replication_enabled"=>true,
       "repositories_synced_count"=>24,
       "repositories_failed_count"=>0,
       "git_fetch_event_count_weekly"=>nil,
       "git_push_event_count_weekly"=>nil,
       ... other geo node status fields
     }
   ]

Implementing Service Ping

See the implement Service Ping guide.

Example Service Ping payload

The following is example content of the Service 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_sha256: "0000000000000000000000000000000000000000000000000000000000000000",
  "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_enabled": false,
  "prometheus_metrics_enabled": false,
  "reply_by_email_enabled": "incoming+%{key}@incoming.gitlab.com",
  "signup_enabled": true,
  "web_ide_clientside_preview_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"
  },
  "container_registry_server": {
    "vendor": "gitlab",
    "version": "2.9.1-gitlab"
  },
  "database": {
    "adapter": "postgresql",
    "version": "9.6.15",
    "pg_system_id": 6842684531675334351,
    "flavor": "Cloud SQL for PostgreSQL"
  },
  "analytics_unique_visits": {
    "g_analytics_contribution": 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": {
    "duration_s": 0.013836685999194742,
    "application_requests_per_hour": 4224,
    "query_apdex_weekly_average": 0.996,
    "failures": [],
    "nodes": [
      {
        "node_memory_total_bytes": 33269903360,
        "node_memory_utilization": 0.35,
        "node_cpus": 16,
        "node_cpu_utilization": 0.2,
        "node_uname_info": {
          "machine": "x86_64",
          "sysname": "Linux",
          "release": "4.19.76-linuxkit"
        },
        "node_services": [
          {
            "name": "web",
            "process_count": 16,
            "process_memory_pss": 233349888,
            "process_memory_rss": 788220927,
            "process_memory_uss": 195295487,
            "server": "puma"
          },
          {
            "name": "sidekiq",
            "process_count": 1,
            "process_memory_pss": 734080000,
            "process_memory_rss": 750051328,
            "process_memory_uss": 731533312
          },
          ...
        ],
        ...
      },
      ...
    ]
  }
}

Notable changes

In GitLab 14.6, flavor was added to try to detect the underlying managed database variant. Possible values are "Amazon Aurora PostgreSQL", "PostgreSQL on Amazon RDS", "Cloud SQL for PostgreSQL", "Azure Database for PostgreSQL - Flexible Server", or "null".

In GitLab 13.5, pg_system_id was added to send the PostgreSQL system identifier.

Export Service Ping SQL queries and definitions

Two Rake tasks exist to export Service Ping definitions.

The Rake tasks export the raw SQL queries for count, distinct_count, sum.
The Rake tasks export the Redis counter class or the line of the Redis block for redis_usage_data.
The Rake tasks calculate the alt_usage_data metrics.

In the home directory of your local GitLab installation run the following Rake tasks for the YAML and JSON versions respectively:

# for YAML export
bin/rake gitlab:usage_data:dump_sql_in_yaml

# for JSON export
bin/rake gitlab:usage_data:dump_sql_in_json

# You may pipe the output into a file
bin/rake gitlab:usage_data:dump_sql_in_yaml > ~/Desktop/usage-metrics-2020-09-02.yaml

Generate Service Ping

To generate Service Ping, use Teleport or a detached screen session on a remote server.

Triggering

Trigger Service Ping with Teleport

Request temporary access to the required environment.
After your approval is issued, access the Rails console.
Run ServicePing::SubmitService.new.execute.

Trigger Service Ping with a detached screen session

Connect to bastion with agent forwarding:
```
ssh -A lb-bastion.gprd.gitlab.com
```
Create named screen:
```
screen -S <username>_usage_ping_<date>
```

Connect to console host:

ssh $USER-rails@console-01-sv-gprd.c.gitlab-production.internal

Run:
```
ServicePing::SubmitService.new.execute
```
To detach from screen, press ctrl + A, ctrl + D.
Exit from bastion:
```
exit
```
Get the metrics duration from logs:

Search in Google Console logs for time_elapsed. Query example.

Verification (After approx 30 hours)

Verify with Teleport

Follow the steps to request a new access to the required environment and connect to the Rails console
Check the last payload in raw_usage_data table: RawUsageData.last.payload
Check the when the payload was sent: RawUsageData.last.sent_at

Verify using detached screen session

Reconnect to bastion:
```
ssh -A lb-bastion.gprd.gitlab.com
```
Find your screen session:
```
screen -ls
```

Attach to your screen session:

screen -x 14226.mwawrzyniak_usage_ping_2021_01_22

Check the last payload in raw_usage_data table:
```
RawUsageData.last.payload
```
Check the when the payload was sent:
```
RawUsageData.last.sent_at
```

Skip database write operations

To skip database write operations, DevOps report creation, and storage of usage data payload, pass an optional argument:

skip_db_write:
ServicePing::SubmitService.new(skip_db_write: true).execute

Monitoring

Service Ping reporting process state is monitored with internal SiSense dashboard.