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Deploy dbt

Use dbt Cloud's capabilities to seamlessly run a dbt job in production or staging environments. Rather than run dbt commands manually from the command line, you can leverage the dbt Cloud's in-app scheduling to automate how and when you execute dbt.

dbt Cloud offers the easiest and most reliable way to run your dbt project in production. Effortlessly promote high quality code from development to production and build fresh data assets that your business intelligence tools and end users query to make business decisions. Deploying with dbt Cloud lets you:

  • Keep production data fresh on a timely basis
  • Ensure CI and production pipelines are efficient
  • Identify the root cause of failures in deployment environments
  • Maintain high-quality code and data in production
  • Gain visibility into the health of deployment jobs, models, and tests
  • Uses exports to write saved queries in your data platform for reliable and fast metric reporting

Before continuing, make sure you understand dbt's approach to deployment environments.

Learn how to use dbt Cloud's features to help your team ship timely and quality production data more easily.

Deploy with dbt​

Job scheduler

The job scheduler is the backbone of running jobs in dbt Cloud, bringing power and simplicity to building data pipelines in both continuous integration and production environments.

Deploy jobs

Create and schedule jobs for the dbt Cloud scheduler to run.

Continuous integration

Set up CI checks so you can build and test any modified code in a staging environment when you open PRs and push new commits to your dbt repository.

Continuous deployment

Set up merge jobs to ensure the latest code changes are always in production when pull requests are merged to your Git repository.

Job commands

Configure which dbt commands to execute when running a dbt job.

Monitor jobs and alerts​

Run visibility

View the history of your runs and the model timing dashboard to help identify where improvements can be made to the scheduled jobs.

Retry jobs

Rerun your errored jobs from start or the failure point.

Job notifications

Receive email or Slack channel notifications when a job run succeeds, fails, or is canceled so you can respond quickly and begin remediation if necessary.

Webhooks

Create outbound webhooks to send events about your dbt jobs' statuses to other systems in your organization.

Artifacts

dbt Cloud generates and saves artifacts for your project, which it uses to power features like creating docs for your project and reporting the freshness of your sources.

Source freshness

Enable snapshots to capture the freshness of your data sources and configure how frequent these snapshots should be taken. This can help you determine whether your source data freshness is meeting your SLAs.

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