Execution History
Track and debug your automation runs
Execution History shows you every time a workflow runs, what path it took, and whether it succeeded or failed. Use it to monitor performance, debug issues, and understand how your automations are working.
Accessing History
- Navigate to Automations in your dashboard
- Click the History tab
- View all recent executions
Or from a specific workflow:
- Open the workflow
- Click History to see only that workflow's executions
History Overview
The history page shows:
- Execution list — All runs with status and timestamp
- Filters — Filter by workflow, status, date range
- Statistics — Success rate, average duration, error rate
Execution Entry
Each execution shows:
| Field | Description |
|---|---|
| Workflow | Name of the workflow that ran |
| Trigger | What event started it |
| Status | Success, failed, or skipped |
| Duration | How long it took |
| Timestamp | When it ran |
| Platform | Which platform triggered it |
Status Types
Success ✓
The workflow completed all actions successfully.
What this means:
- Trigger received and processed
- All conditions evaluated
- All actions executed without error
Failed ✗
The workflow encountered an error and stopped.
Common reasons:
- API rate limit exceeded
- Token expired or revoked
- Platform API error
- Invalid action configuration
Skipped ⊘
The workflow was triggered but took no action.
Common reasons:
- Condition evaluated to "No"
- No actions connected to the path taken
- Workflow was disabled during execution
Execution Details
Click any execution to see full details:
Trigger Data
The complete event that triggered the workflow:
{
"type": "trigger.comment",
"platform": "instagram",
"channelId": "ch_abc123",
"timestamp": "2025-01-15T10:30:00Z",
"comment": {
"id": "17891234567890",
"text": "What's the price?",
"authorId": "12345678",
"authorName": "user_example",
"postId": "17891234567891"
}
}Execution Trace
Step-by-step log of what happened:
[10:30:00.100] Trigger: Comment Received
↳ comment.text = "What's the price?"
↳ platform = instagram
[10:30:00.150] Condition: Text Contains
↳ keywords = ["price", "cost", "how much"]
↳ result = YES (matched "price")
[10:30:00.200] Action: Reply
↳ template = "Our prices start at $99..."
↳ status = SUCCESS
↳ replyId = "17891234567899"Error Details
If the execution failed, you'll see:
- Error type — What kind of error
- Error message — Specific error text
- Failed step — Which node failed
- Stack trace — Technical details (for debugging)
Error: Rate limit exceeded
Failed at: Action (Reply)
Message: Instagram API rate limit (200/hour) exceeded
Retry: Will retry in 45 minutesFiltering History
By Status
- All — Show everything
- Success — Only successful runs
- Failed — Only errors
- Skipped — Only no-action runs
By Workflow
Select a specific workflow to see only its executions.
By Date Range
- Last hour — Recent activity
- Last 24 hours — Today's runs
- Last 7 days — Weekly view
- Custom range — Specific dates
By Platform
Filter to see executions from specific platforms.
Metrics & Statistics
The history page shows aggregate statistics:
| Metric | Description |
|---|---|
| Total executions | Number of times workflows ran |
| Success rate | Percentage that completed successfully |
| Average duration | How long executions typically take |
| Error rate | Percentage that failed |
| Most active workflow | Which workflow runs most often |
Charts
Visual representations of:
- Executions over time — Volume trends
- Status distribution — Success/fail/skip ratio
- Platform breakdown — Which platforms trigger most
- Workflow comparison — Performance by workflow
Debugging Failed Executions
Step 1: Identify the Error
- Find the failed execution
- Click to open details
- Read the error message
- Identify which step failed
Step 2: Understand the Cause
Rate limit errors:
- Too many API calls in short time
- Solution: Reduce workflow frequency or wait
Token errors:
- OAuth token expired or revoked
- Solution: Reconnect the channel
API errors:
- Platform rejected the request
- Solution: Check action configuration
Configuration errors:
- Invalid settings in node
- Solution: Review and fix workflow
Step 3: Fix the Issue
- Open the workflow
- Navigate to the failed node
- Review configuration
- Make corrections
- Test the workflow
- Re-enable if needed
Step 4: Verify the Fix
- Wait for next trigger
- Check execution history
- Confirm success
Retrying Failed Executions
Some failures can be retried:
- Open the failed execution
- Click Retry (if available)
- Execution runs again with same trigger data
Retry not available when:
- The trigger event is too old
- The error is not retriable (configuration error)
- The workflow has been deleted
Exporting History
Export execution history for analysis:
- Apply filters for desired data
- Click Export
- Choose format (CSV or JSON)
- Download file
Export includes:
- Execution ID
- Workflow name
- Trigger type
- Status
- Timestamp
- Duration
- Error details (if failed)
History Retention
Execution history is retained for:
| Plan | Retention |
|---|---|
| Free | 7 days |
| Pro | 30 days |
| Business | 90 days |
| Enterprise | 1 year |
Older executions are automatically deleted.
Monitoring Best Practices
Daily Check
Spend 5 minutes reviewing:
- Any new failures?
- Unusual patterns?
- High error rate?
Weekly Review
Look at aggregate metrics:
- Success rate trending up or down?
- Any workflows consistently failing?
- Volume matching expectations?
Set Up Alerts
Configure notifications for:
- Execution failures
- High error rates
- Rate limit warnings
Document Issues
Keep a log of:
- Recurring problems
- Solutions that worked
- Patterns you notice
Troubleshooting Common Patterns
Sudden Spike in Failures
Possible causes:
- Platform API outage
- Token expiration
- Rate limit reached
- Workflow misconfiguration
Investigation:
- Check if all workflows affected or just one
- Check platform status pages
- Review error messages
- Check token status in Channels
Gradual Increase in Errors
Possible causes:
- Growing volume hitting rate limits
- Token about to expire
- Platform policy changes
Investigation:
- Compare volume over time
- Check rate limit usage
- Review platform announcements
Inconsistent Behavior
Possible causes:
- Platform-specific differences
- Edge cases in conditions
- Variable data issues
Investigation:
- Compare successful vs failed runs
- Look for patterns in trigger data
- Test with specific inputs