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Open a run from a schedule’s run history to see what happened: the pipeline, the executed nodes, timing, and per-command logs.

Overview

The header shows the run number, its status, and when it ran. A metadata row shows the date, duration, trigger, owner, branch and commit, SLA, and self-healing. A run on a different branch from its schedule’s own branch, or on a commit that isn’t on that branch, shows a Branch override pill, and its run after schedules don’t start. The stats panel shows the Succeeded, Errors, and Skipped counts.

Run views

Switch between three views of the run:
  • Pipeline — the commands as a DAG, each with its status.
  • Executed nodes — the individual dbt™ objects (models, tests, and so on) the run built.
  • Model timeline — models over time, to spot long-running or bottleneck models.

Retry

If a run fails, click Retry to resume from the failed command or re-run every command. Each retry creates a new run and leaves the original intact. Turbo CI and merge runs are steps of a chain, so Retry offers Retry this step or Retry the whole chain instead. See Retrying a run.

Cancel a run

Click Cancel Run to stop a run that is still going. A run also stops this way when you cancel it from the API, or when a newer Turbo CI run replaces it.
  • dbt™ commands stop cleanly. Bolt interrupts dbt™ and gives it up to 60 seconds to cancel the queries it has running in your warehouse. This is dbt™‘s own cancel, so it works on any adapter that supports it. On BigQuery, it needs dbt™ 1.9 or later. Before, queries could keep running, and billing, after the run stopped.
  • Other commands stop at once.
  • No more commands start. The commands after the one that was running don’t run.
  • The run shows Canceled right away. It sends no notifications and starts no run after schedules.

Logs and artifacts

Each command in the run has an AI summary, full logs, and downloadable artifacts. See Run logs and artifacts.