Setup Slack Integration

Before you start

Before you can start using the alerts, make sure to install the dbt package, configure a profile and install the CLI. This is required for the alerts to work.


First create a Slack app:

Based on the method you selected, create a token or webhook:

Lastly, pass the token / webhook to the CLI as a param or in the config.yml file:

Execute the CLI

Make sure to run the following command after your dbt runs and tests:

edr monitor --slack-token <your_slack_token> --slack-channel-name <slack_channel_to_post_at> --group-by [table | alert]

Or just edr monitor if you used config.yml. Please note that when you specify the —slack-channel-name, it’s the default channel name to which all the alerts will be sent that are not attributed to any custom channel. Therefore, if you execute several edr monitor commands at the same time with different slack-channel-name arguments, they can be sent to the wrong one due to the overlap accessing the backend table of elementary. For avoiding this problem, the guide can be followed.


Alert on source freshness failures

Not supported in dbt cloud

To alert on source freshness, you will need to run edr run-operation upload-source-freshness right after each execution of dbt source freshness. This operation will upload the results to a table, and the execution of edr monitor will send the actual alert.

  • Note that dbt source freshness and upload-source-freshness needs to run from the same machine.
  • Note that upload-source-freshness requires passing --project-dir argument.

Continuous alerting

In order to monitor continuously, use your orchestrator to execute it regularly (we recommend running it right after your dbt job ends to monitor the latest data updates).

Read more about how to deploy Elementary in production. If you need help or wish to consult on this, reach out to us on Slack.