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.
Learn how to create and schedule deploy jobs in dbt Cloud for the scheduler to run. When you run with dbt Cloud, you get built-in observability, logging, and alerting.
We have enhanced the dbt Cloud Scheduler by reducing prep time for all accounts and provided unlimited job concurrency for Enterprise accounts.
October 2023: Rerun errored jobs from start or from the failure point
The dbt Cloud job scheduler queues scheduled or API-triggered runs, before preparing the job to enter cloud data platform. Build observability into transformation workflows with the in-app scheduling, logging, and alerting.
Learn about the different job types in dbt Cloud and what their differences are.
Monitor your dbt Cloud job and set up alerts to ensure seamless orchestration and optimize your data transformations
dbt Labs is making a change to the metadata retrieval policy for Run History in dbt Cloud.
New usability and design improvements to the run details and logs in dbt Cloud are now available. The ability to triage errors in logs is a big benefit of using dbt Cloud's job and scheduler functionality. These updates help make the process of finding the root cause much easier.
New usability and design improvements to the Run History dashboard in dbt Cloud are now available. These updates allow people to discover the information they need more easily by reducing the number of clicks, surfacing more relevant information, keeping people in flow state, and designing the look and feel to be more intuitive to use.
Monitor your jobs to make performance improvements.
April 2023: