What this category of data looks like
This content is compatible with FastGPT v4.17.0. Data sources for this category include fault timelines, system logs, monitoring metrics, and code commit records. Update frequency is either after each major incident or once per month. Daily deliverables include RCA reports, incident tickets, review minutes, and rectification tracking forms. Data fields include fault occurrence timestamp, root cause description, rectification measures, and associated session identifier. Units include timestamps, character counts, and execution status identifiers. Document structure uses layered archiving based on incident review workflows to support subsequent root cause analysis and compliance auditing.
What constraints these characteristics impose on conversation logs and auditing
Low update frequency paired with full linked full-stack incident information requires that conversation log auditing fully retains all interactions associated with incident-related sessions, and must not truncate key verification steps. Layered archived document characteristics require that audit logs are bound to the unique identifiers of corresponding RCA reports and incident tickets, to enable cross-document traceability. Most data sources are operation and maintenance and code-related technical records, requiring audit fields to be compatible with technical identifiers such as timestamps and status codes, rather than relying solely on business text fields. Large associated data volume for a single incident requires the auditing workflow to support batch retrieval of session logs by incident ID.
How to configure settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Prefix with incident ticket ID, format fault-{faultId}-{chatId} | Facilitates linking incident tickets and RCA reports for this category, enabling one-click traceability between sessions and incidents |
responseChatItemId | Number consecutively per session interaction sequence, starting value 1 | Matches root cause analysis hypothesis verification workflows, enabling backtracking of the verification process for each step of the conversation |
detail | Retain full interaction text, including user questions, model responses, and system prompts, maximum storage 8000 characters | Meets evidence collection requirements for root cause hypothesis verification, retains full interaction details |
| Session log retention period | 12 months | Matches general auditing cycle requirements for enterprise security and compliance |
| Log retrieval threshold | Calibrated via actual testing, single retrieval returns no more than 200 records | Avoids excessive data slowing down root cause analysis verification efficiency |
| Audit trigger condition | Automatically trigger log archiving when an incident ticket creation event occurs | Matches the incident review update rhythm of this category, ensuring no data is missed |
Three common misconfigurations
- Symptom: Login-free session windows cannot view historical conversation records, but full interactions can be retrieved in backend logs. Cause: The
chatIdof login-free sessions is not bound to the user identifier field, causing the frontend to fail to match session access permissions. - Symptom: A
cannot read properties of undefined (reading)error is thrown when testing the Qwen model on a new channel. Cause: The storage path of thedetailfield is not configured correctly, causing the system to fail to parse uninitialized interaction content when reading logs. - Symptom: A page error occurs when viewing session log details, and complete conversation content fails to load. Cause: A reasonable log retrieval threshold is not set, and the single return data volume exceeds the frontend rendering limit.
How to confirm configuration is complete
- Retrieve the unique identifier of the corresponding incident ticket, confirm that associated interaction records can be matched in the session log list.
- View the
detailfield of a single session, confirm that it contains complete user questions, model responses, and system prompt content. - Trigger an incident ticket creation event, confirm that the system automatically generates associated audit log entries.
- Test the log access permissions of login-free sessions, confirm that the frontend can normally load historical records of the corresponding session.
Note: The values listed above are common starting points and should be evaluated against your own specific samples and use cases.
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.