> ## Documentation Index
> Fetch the complete documentation index at: https://lightdash-mintlify-60f0f1de.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Preview local changes

> Preview projects are temporary Lightdash projects where you can safely experiment with your metrics, dimensions and charts without affecting your production project.

Preview projects will copy all spaces/charts/dashboards into your new preview project, so you can test the content and also run [validation](/guides/cli/how-to-use-lightdash-validate). This is only copied on preview creation, you can't sync the content afterwards.

### Run `lightdash preview` from inside your project

```bash theme={null}
# This will create a preview and will wait until you press a key to delete the preview project
lightdash preview
```

or

```bash theme={null}
# This will create a preview and exit, you will have to run lightdash stop-preview to delete it
lightdash start-preview
```

Then `cmd` + `click` to open the preview link from your terminal. Once you're in Lightdash go to `Explore` --> `Tables`, then click on the model(s) you just updated to see your changes and play around with them.

<Tip>
  **Updating your preview while it's running**

  While your preview is running, you can run `dbt compile` in a separate terminal session to update your dbt models. After compiling, refresh your browser to see the changes in Lightdash. Note that this is not a hot reload - you need to manually refresh the page.
</Tip>

<Info>
  **Problems with credentials?**

  When you create preview projects, Lightdash will use the same warehouse connection settings you have in your `profiles.yml` file for your current dbt project. This can be a problem if you're using a local database that your laptop can reach but your Lightdash instance cannot.
</Info>

### Redshift with `method: iam`

If your dbt Redshift profile authenticates with `method: iam`, `lightdash preview` resolves an AWS identity from your local AWS credential chain and forwards the resulting access key ID, secret access key, and (if present) session token to the backend. The backend then uses them to mint short-lived Redshift credentials per query, but **only for the preview project**.

* If `iam_profile` is set on the dbt target, the CLI resolves credentials from that profile (`fromIni`), matching dbt's own precedence. This covers AWS SSO profiles.
* Otherwise the CLI walks the default provider chain (`fromNodeProviderChain`): environment variables, the default profile, SSO, then an instance role.
* If the chain resolves nothing, `lightdash preview` fails fast with an actionable error pointing at `aws sso login` (or configuring a profile) rather than creating a broken preview.

The common workflow is signing in with SSO and then starting a preview — no long-lived per-user AWS keys required:

```bash theme={null}
aws sso login --profile my-redshift-profile
lightdash preview
```

Because SSO and role credentials are short-lived, the CLI prints a warning showing the expiry when it forwards temporary credentials. Queries in the preview project will stop working once the session expires — re-run `aws sso login` and `lightdash preview` to refresh them.

<Note>
  This applies to ephemeral preview projects created from your local dbt profile. For a durable, persistent project connection to Redshift with IAM, use a role the Lightdash backend assumes (`assumeRoleArn`) — see [Connect Redshift](/get-started/setup-lightdash/connect-project#redshift).
</Note>