Overview
Sona's Workflows > History section is your complete log of past workflow runs, giving you visibility into every automation that has been executed in your account. This helps you monitor performance, troubleshoot issues, and ensure your workflows are running as expected. With this guide, you will be ready to confidently track and analyze your workflow activity.
When to use Workflows: History
Use the History section when you need to:
Verify that a workflow ran successfully.
Troubleshoot failed workflow executions.
Monitor workflow performance over time.
Review past automation activity for reporting or analysis.
Check execution timing and duration patterns.
How Workflows: History works
Here is what happens behind the scenes:
Workflow Execution: when a workflow runs, either manually triggered or automatically, it performs its designated actions using AI agents.
Data Processing: the workflow processes your data, takes actions, and potentially returns results.
Execution Recording: once complete, successfully or with errors, the execution details are automatically logged.
History Display: all execution records are then displayed in your History section with key details like duration, status, and resource usage.
This gives you complete visibility into your data activation processes: you can see exactly what happened, when it happened, and how your AI workflows are performing over time.
Step 1: accessing your workflow history
Navigate to History: from the left sidebar, click History under the Workflows section. You will see a comprehensive list of all workflow executions.
Understanding the History display: each workflow execution shows:
Name: the workflow that was executed, for example "My workflow 4".
Status: Success (green) or Error (red) indicators.
Duration: how long the execution took, shown in seconds.
Date: when the workflow was executed, in YYYY-MM-DD format.
Credits: the number of credits consumed during execution.
Step 2: filtering and searching your history
Use the search function: enter workflow names or keywords in the Search history box, then click the blue Search button to filter results.
Filter by status: use the Filter by status dropdown to show only successful or failed executions, which helps quickly identify problematic workflows.
Filter by date range: click Filter by date to narrow results to specific time periods, perfect for monthly reports or troubleshooting recent issues.
Step 3: analyzing execution results
Review successful executions:
A green Success status indicates the workflow completed without errors.
Note the duration to understand performance patterns.
The Credits column shows how many credits were consumed.
Investigate failed executions:
A red Error status signals something went wrong.
Check the credit usage; higher numbers may indicate where the failure occurred.
Compare with successful runs to identify patterns.
Key concepts and best practices
Understanding execution status:
Success: the workflow completed all steps without errors.
Error: the workflow encountered an issue and stopped execution.
Duration: measured in seconds; longer times may indicate complex processing or potential bottlenecks.
FAQs
What does the Workflows History section show?
What does the Workflows History section show?
Workflows History is a complete log of every past workflow run in your account. Each entry shows the workflow name, its Success or Error status, how long it took, when it ran, and how many credits it consumed, so you can monitor performance and troubleshoot issues.
How do I investigate a failed workflow run?
How do I investigate a failed workflow run?
Use the Filter by status dropdown to isolate executions marked Error, then check the credit usage for each one, since higher numbers may indicate where the failure occurred. Comparing failed runs against successful ones can help you identify patterns.
What does the Credits column measure?
What does the Credits column measure?
The Credits column shows how many credits a workflow execution consumed. Reviewing credit usage alongside duration and status helps you understand performance patterns and spot executions that may have failed partway through.




