Telemetry

dlt collects and reports anonymous usage information. This information is essential to figure out how we should improve the library. Telemetry does not send any personal data. We create random tracking cookie that is stored in your ~./dlt directory. You can disable telemetry at any moment or send it to your own servers instead.

How to opt-out

You can disable telemetry by adding --disable-telemetry to any dlt command.

This command will disable telemetry both in the current project and globally for the whole machine:

dlt --disable-telemetry

While this command will also permanently disable telemetry and then initialize the chess pipeline:

dlt --disable-telemetry init chess duckdb

You can check the current telemetry status with this command:

dlt telemetry

The other way to disable telemetry is to set the runtime.dlthub_telemetry option in config.toml file in .dlt folder.

[runtime]

dlthub_telemetry=false

What we send when

Anonymous telemetry is sent when:

• Any dlt command is executed from the command line. The data contains the command name. In the case of dlt init command, we also send the requested destination and data source names.
• When pipeline.run is called, we send information when extract, normalize and load steps are completed. The data contains the destination name (e.g. duckdb), hashes of: dataset name, pipeline name, default schema name, destination fingerprint (which is a hash of selected destination configuration fields), elapsed time, and if the step succeeded or not.
• When dbt and airflow helpers are used

Here is an example dlt init telemetry message:

{
  "anonymousId": "933dd165453d196a58adaf49444e9b4c",
  "context": {
    "ci_run": false,
    "cpu": 8,
    "exec_info": [],
    "library": {
      "name": "dlt",
      "version": "0.2.0a25"
    },
    "os": {
      "name": "Linux",
      "version": "4.19.128-microsoft-standard"
    },
    "python": "3.8.11"
  },
  "event": "command_init",
  "properties": {
    "destination_name": "bigquery",
    "elapsed": 3.1720383167266846,
    "event_category": "command",
    "event_name": "init",
    "pipeline_name": "pipedrive",
    "success": true
  }
}

Example for load pipeline run step:

{
  "anonymousId": "570816b273a41d16caacc26a797204d9",
  "context": {
    "ci_run": false,
    "cpu": 3,
    "exec_info": [],
    "library": {
      "name": "dlt",
      "version": "0.2.0a26"
    },
    "os": {
      "name": "Darwin",
      "version": "21.6.0"
    },
    "python": "3.10.10"
  },
  "event": "pipeline_load",
  "properties": {
    "destination_name": "duckdb",
    "destination_fingerprint": "",
    "pipeline_name_hash": "OpVShb3cX7qQAmOZSbV8",
    "dataset_name_hash": "Hqk0a3Ov5AD55KjSg2rC",
    "default_schema_name_hash": "Hqk0a3Ov5AD55KjSg2rC",
    "elapsed": 2.234885,
    "event_category": "pipeline",
    "event_name": "load",
    "success": true,
    "transaction_id": "39c3b69c858836c36b9b7c6e046eb391"
  }
}

The message context

The message context contains the following information:

• anonymousId: a random tracking cookie stored in ~/.dlt/.anonymous_id.
• ci_run: a flag indicating if the message was sent from a CI environment (e.g. Github Actions, Travis CI).
• cpu: contains number of cores.
• exec_info: contains a list of strings that identify execution environment: (e.g. kubernetes, docker, airflow).
• The library, os, and python give us some understanding of the runtime environment of the dlt.

Sending telemetry data to your own Segment instance

You can send the anonymous telemetry information to your own Segment account. You need to create a HTTP Server source and generate a WRITE KEY, which you then pass to the config.toml like this:

[runtime]

dlthub_telemetry_segment_write_key="<write_key>"