What this category of data looks like
This category of data primarily comes from the customer’s ITSM system, monitoring platforms, asset inventories, and on-duty records. Daily associated documents include on-site daily reports, service desk tickets, inspection reports, and SLA monthly reports. Most data updates occur daily; some SLA statistics are updated monthly. Common data fields include ticket number, on-site engineer ID, event occurrence time, processing steps, and result feedback. Units are mostly counts and hours, while SLA-related fields use percentage units. No additional non-standard statistical fields are included.
Constraints imposed by these characteristics on conversation logs and auditing workflows
Data for this category is scattered across the customer’s existing ITSM, monitoring platforms, and other systems. The conversation logs and auditing workflow must support importing multi-source heterogeneous format logs, and must support binding associated fields such as ticket numbers and on-site engineer IDs. Daily updated inspection records and service desk tickets require log synchronization to complete no later than 1 hour after the event occurs. The associated statistical requirements for on-site daily reports and SLA monthly reports require audit logs to retain field mapping rules, and support filtering by custom dimensions defined by the customer’s IT department. In multi-role access scenarios, log viewing permissions for on-site engineers, service managers, and customer IT personnel must be differentiated to prevent leakage of sensitive operations and maintenance data.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Conversation log storage duration | 180 days | Matches the monthly statistical cycle of on-site daily reports and SLA monthly reports, meets regular auditing requirements |
| Log auto-cleanup trigger threshold | 80% disk usage | Prevents log storage from exhausting server resources, adapts to disk capacity in operations and maintenance scenarios |
| Log field mapping rules | Bind ticket number, engineer ID | Matches the association requirements of daily documents for this category, facilitates subsequent statistics and aggregation |
| Multi-role permission isolation | Group by user role | Differentiates viewing permissions for on-site engineers, service managers, and customer IT personnel |
| Log synchronization frequency | Within 1 hour | Matches the synchronization requirements for daily updated inspection and ticket data |
| Audit log export format | CSV, JSON | Compatible with the import formats of the customer’s existing ITSM systems, facilitates data integration |
Three common configuration mistakes
- Symptom: Conversation log query results include historical records from unauthorized users, and the
chatIdfield is not associated with the corresponding engineer ID. Cause: The binding rule betweenchatIdand on-site engineer ID was not configured, resulting in logs not being isolated by user dimension. - Symptom: The audit log module reports an error after startup, prompting a database connection exception. Cause: The conversation log storage was not pointed to the database instance compatible with the customer’s existing ITSM system, resulting in failure to write data normally.
- Symptom: The number of archived conversation logs exceeds the expected upper limit, and automatic cleanup cannot be performed per cycle. Cause: No trigger condition was set for log auto-cleanup, only manual cleanup was available.
How to verify successful configuration
- Log in to the FastGPT backend, enter the conversation log management page, filter by a specified on-site engineer ID, and confirm that only conversation records for that engineer are returned.
- Import a simulated service desk ticket data, check whether the audit log automatically associates the ticket number field, and whether the field mapping conforms to the preset rules.
- Manually trigger a log cleanup operation, confirm that expired logs are properly deleted, and that disk usage matches the preset threshold.
- Check the system version identifier, confirm that the currently running version is FastGPT v4.17.0.
The values provided here are common starting points and should be evaluated against the reader’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.