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lightdash deploy syncs the changes in your dbt project to Lightdash

If you’ve made some changes to your dbt project and you’d like to make them available in your Lightdash project, you can easily do this using the lightdash deploy command in the Lightdash CLI tool.

git checkout main # checkout main or master - or whatever your production branch name is where you've merged your changes
git pull
lightdash deploy # --target prod. If you use developer profiles in your dbt project, you might need this flag. See below.

This will deploy the changes in your dbt project to the Lightdash project you set up on your CLI tool earlier.

Lightdash’s deploy command will deploy using your default dbt profile unless you specify to use a different target.

For example, if you’ve set up a developer profile where it targets a dev dataset (like dbt_khindson.my_model_names), then you’ll need to pass the production target in your lightdash deploy command. Something like: lightdash deploy --profile prod.

And voilà! Once it’s completed click the URL to head straight to your project where your changes will be ready to be explored.

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Automatically deploy your changes to Lightdash using a GitHub action

If you’ve connected Lightdash to GitHub, you can setup a github action and get Lightdash to deploy your project automatically. This is the easiest way to keep Lightdash in sync with your changes in dbt.

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Step 1: add the credentials to Github secrets

We are going to add some secrets and config to GitHub actions, but you don’t want those to be public, so the best way to do this is to add them as secrets on Github.

If you already have a GitHub action for Lightdash, then you can use the same Lightdash secrets you created for your other action.

Go to your repo, click on Settings , on the left sidebar, click on Secrets under Security. Now click on the New repository secret

We need to add the following secrets:

LIGHTDASH_API_KEY

Create a new personal access token, by going to Settings > Personal Access Tokens. This is the token you’ll put in for LIGHTDASH_API_KEY.

LIGHTDASH_PROJECT

The UUID for your project. For example, if your URL looks like https://eu1.lightdash.cloud/projects/3538ab33-dc90-aabb-bc00-e50bba3a5f69/tables, then 3538ab33-dc90-45f0-aabb-e50bba3a5f69 is your LIGHTDASH_PROJECT

LIGHTDASH_URL

This is either https://eu1.lightdash.cloud or https://app.lightdash.cloud for Lightdash Cloud users (check the URL to your Lightdash project). If you self-host, this should be your own custom domain.

DBT_PROFILES

Some tips for this bit:

  • You might be able to copy a bunch of the information from your local profiles.yml file. You can see what’s in there by typing cat ~/.dbt/profiles.yml in your terminal.
  • If you have a separate prod and dev profile, you probably want to use the information from your prod profile for your GitHub action.
  • If you want to have different connection settings depending on the user that opened the pull request (dev profiles), then check out this guide.

Find your data warehouse from the list below to get a profiles.yml file template. Fill out this template, and this is your DBT_PROFILES secret.

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Step 2: Create deploy.yml workflow in Github

Go to your repo, click on Actions menu.

If you don’t have any GitHub actions, you’ll just need to click on Configure

If you have some GitHub actions in your repo already, click on New workflow, then select setup a workflow yourself.

Now copy this file from our cli-actions repo.

Give it a nice name like deploy-lightdash.yml

And commit this to your repo by clicking on Start commit.

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You’re done!

Everytime you make a change to your repo, on the main branch, it will automatically deploy your new config into your Lightdash projects

You can see the log on the Github actions page

Raise issue