Run history

Run history is the main operational view for a live Journey.

Run history page showing an empty state with the message Your run history will appear here
Run history β€” each execution appears here with its status, timestamp, and run type after the Journey is published and runs.

What run history shows

Each row in the run history table represents one execution of the Journey. The table shows:

Column
Description

Started

Timestamp when the run began

Status

Success or Fail

Run type

Whether the run was scheduled or triggered manually

What run history helps you answer

  • Did the run succeed or fail?

  • When did it happen?

  • Was it manual (Run now or Full run) or part of the normal schedule?

  • Is there a recent failure that needs attention?

  • Did a failure coincide with a recent configuration change?

When to check run history

Situation
Why

After publishing a Journey

Confirm the first run started and completed successfully

After running manually

Confirm the manual run produced the expected result

Before resuming a paused Journey

Check whether there were failures before the pause

When business results look unexpected

Correlate Journey runs with the period where results diverged

After a configuration change

Confirm the change did not introduce a failure

How to read a run

A successful run means the Journey completed its execution cycle without errors. It does not guarantee that contacts entered or that destinations were activated β€” it means the orchestration ran as expected.

A failed run means an error occurred during execution. Check the run details to understand the failure before retrying or resuming.

Good operating habits

Check immediately after launch. The first run after publishing is the most important one to review. Confirm it started, completed, and that entry volume looks reasonable.

Review failures before editing. If the most recent run is a failure, understand why before making changes to the Journey. The failure may be caused by a configuration issue that your edit will not address.

Capture the failure context before retrying. Note the timestamp and any error details before taking action. This helps you explain what happened if the issue recurs.

Track entry volume over time. Significant changes in the number of contacts entering per run can indicate a problem with the entry rule or the underlying audience. An unexpectedly large entry volume may mean more contacts are being activated than intended.

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