This document applies to FastGPT v4.17.0.
What this category of data looks like
This category of data includes four core document types: service requests, incident tickets, processing records, and user satisfaction surveys. Data sources include enterprise ITSM systems, user phone or chat records, asset systems, and internal knowledge bases. Data update frequencies are divided into real-time and daily updates. Real-time data corresponds to newly submitted tickets and immediate processing records. Daily update data corresponds to batch-summarized satisfaction statistics and asset association information. Core fields include ticket ID, submitter identifier, problem category, processing status, response duration, and satisfaction score. Field types cover strings, enumerations, duration values, and score ranges.
What constraints these characteristics impose on database and operations workflows
Multi-source data access requires the database to support hybrid deployment of structured and unstructured storage. It must adapt separately to structured ticket fields and unstructured content such as chat records and processing logs. Real-time updated ticket data creates high concurrent access pressure. Connection pool parameters must be configured appropriately to avoid resource exhaustion. Data from different sources must be stored using unified field mapping rules to ensure consistency across systems. Data anomalies in this category directly impact employee work and service SLA compliance. Therefore, database operations must support high availability and rapid recovery. They must also support fine-grained permission control to ensure data security.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:xxxx@db-host:27017/it_service_ticket?authSource=admin | Used to store unstructured ticket chat records and processing logs, adapting to storage needs for multi-source unstructured data |
PG_URL | postgresql://fastgpt:xxxx@db-host:5432/it_service_db?sslmode=require | Used to store structured ticket fields and user satisfaction data, supporting complex classification and statistical queries |
DB_MAX_LINK | 20–50 | Matches concurrent request volumes for daily IT service desk tickets, preventing service interruptions caused by exhausted database connections |
REDIS_URL | redis://:xxxx@redis-host:6379/0 | Used to cache frequently queried ticket categories and user common problem data, reducing repeated query load on the database |
Three common configuration errors
- Symptom: A database connection prompt indicates IP is not authorized, and ticket data cannot be read or written. Cause: The external request IP of the FastGPT deployment node was not added to the database whitelist, resulting in access being blocked by the database.
- Symptom: A syntax error is returned when executing multi-line SQL statements, and ticket status cannot be updated in batches. Cause: Multi-line query support for database connections was not enabled, or the statement delimiter was not configured correctly, preventing a single connection from executing multiple SQL commands.
- Symptom: After restoring a project backup, ticket data is not fully restored, and only agent and knowledge base configurations are recovered. Cause: Only project configuration files were backed up, and associated database data was not synchronized for backup, resulting in loss of core ticket data.
How to confirm configurations are valid
- Run the built-in database connection test tool to verify that ticket lists can be read normally and new processing records can be written
- View the database connection pool monitoring panel to confirm that the current active connection count does not exceed the configured
DB_MAX_LINKthreshold - Trigger a real ticket submission process to check whether data is correctly written to the ticket table and log table of the corresponding database
- Simulate a database connection interruption scenario to confirm that the service can automatically reconnect and restore normal ticket processing capabilities
The values provided here are common starting points and should be measured 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.