How Syncs Work
A sync is the process of transferring data between connected systems based on your mapping configuration. This guide explains the sync lifecycle, what happens during a sync, and how to monitor sync health.
The Sync Lifecycle
Every sync follows these stages:
1. PENDING → Sync is queued and waiting to start
2. RUNNING → Sync is actively processing records
3. COMPLETED → Sync finished successfully
PARTIAL → Sync finished but some records failed
FAILED → Sync could not complete
What Happens During a Sync
Stage 1: Initialization
FluxCascade prepares for the sync:
- Load the mapping configuration
- Verify connections to both systems are active
- Retrieve access tokens (refreshing if needed)
- Determine which records need syncing
Stage 2: Data Fetch
Records are retrieved from the source system:
- Full Sync: All records matching the mapping criteria
- Incremental Sync: Only records modified since last sync
- Webhook-Triggered: The specific record(s) that changed
Stage 3: Transformation
For each record, FluxCascade:
- Maps source fields to target fields
- Applies configured transformations
- Validates required fields are present
- Checks for conflicts (bidirectional syncs)
Stage 4: Upsert
Records are written to the target system:
- Create: New records not found in target
- Update: Existing records with changes
FluxCascade uses "upsert" logic to handle both cases automatically.
Stage 5: Completion
After processing all records:
- Success/failure counts are tallied
- Sync status is updated
- Audit log is written
- Notifications are sent (if configured)
Sync Types
Manual Sync
Triggered on-demand by clicking Sync Now:
- Useful for testing new mappings
- Good for one-time data migrations
- Full control over when syncs occur
Scheduled Sync
Runs automatically on a schedule:
| Frequency | Best For |
|---|---|
| Every 15 minutes | High-frequency updates, active teams |
| Hourly | Standard sync needs, balanced approach |
| Daily | Low-volume data, nightly batch processing |
| Weekly | Report data, archival syncs |
See Scheduling for configuration details.
Webhook-Triggered Sync
Runs immediately when data changes:
- Near real-time synchronization
- Only processes changed records
- Most efficient for active data
See Webhooks for setup instructions.
Sync Statistics
Each completed sync reports:
| Statistic | Description |
|---|---|
| Records Processed | Total records evaluated for sync |
| Created | New records added to target system |
| Updated | Existing records modified |
| Skipped | Records unchanged or filtered out |
| Failed | Records that could not be synced |
| Duration | Time taken to complete the sync |
Viewing Sync History
Syncs Page
Navigate to Syncs in the sidebar to see:
- All recent sync jobs across mappings
- Filter by status, mapping, or date range
- Quick stats and status indicators
Mapping Detail View
Click on a mapping to see:
- Sync history for that specific mapping
- Success rate over time
- Last sync details
Individual Sync Details
Click on any sync job to view:
- Full statistics breakdown
- Record-by-record results
- Error details for failed records
- Timestamps and duration
Sync Logs
Each sync generates detailed logs:
Event Log
Chronological events during the sync:
14:30:00 - Sync started
14:30:01 - Connected to HubSpot
14:30:01 - Connected to Jobber
14:30:02 - Fetched 150 contacts from HubSpot
14:30:05 - Processed 150 records
14:30:05 - Created 12, Updated 45, Skipped 93
14:30:05 - Sync completed successfully
Error Log
Details on failed records:
Record: john@example.com
Error: Invalid phone format - could not parse "(555) ABC-1234"
Field: phone
Action: Skipped field, synced other fields
Running a Manual Sync
From the Syncs Page
- Click + New Sync
- Select the mapping to sync
- Choose sync options:
- Full sync or incremental
- Test mode (preview only)
- Click Start Sync
From a Mapping
- Open the mapping
- Click the Sync Now button (⚡)
- Confirm to start
From the Dashboard
Use the quick sync buttons on your dashboard to trigger syncs for active mappings.
Sync Performance
Factors Affecting Speed
- Record count: More records = longer sync
- Field count: More fields per record = more processing
- API rate limits: External systems may throttle requests
- Transformations: Complex transforms add processing time
Optimization Tips
- Use incremental syncs – Only sync changed records
- Enable webhooks – Process records as they change
- Limit fields – Only map fields you need
- Schedule wisely – Balance frequency with performance
Next Steps
- Scheduling – Configure automatic syncs
- Webhooks – Enable real-time sync
- Error Handling – Handle sync failures