What this category of data looks like
Data for this category comes from scheduling systems, fault tickets, monitoring alerts, and organizational contact directories. Updates occur daily or weekly. Core documents include shift schedules, handover records, escalation contact lists, and daily shift reports. Each document type includes specific fields:
- Shift schedules include date, on-duty personnel, and contact information
- Handover records include unfinished tasks, pending fault handling, and escalation paths
- Escalation contact lists include position, name, and emergency contact information
- Daily shift reports include daily fault handling status and summary of handover items
Constraints for database and operations maintenance
Diverse data sources include both document-type and structured data. Database configurations must support connection requirements for different storage engines. The daily or weekly update frequency requires database connections to support incremental synchronization or scheduled full synchronization, to avoid reloading full datasets repeatedly. Core documents have multiple associated fields. Add constraints for key fields to prevent conflicts. Cache frequently queried on-duty personnel contact information and daily escalation paths to reduce database load. Match connection pool configuration to average daily read/write request volume to avoid service interruptions from exhausted connections.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/database?authSource=admin | Supports storage needs for unstructured handover records and temporary shift adjustment notes |
PG_URL | postgresql://user:pass@host:5432/fastgpt?schema=public | Stores structured documents with clear fields such as shift schedules, escalation contact lists, and daily shift reports |
DB_MAX_LINK | 15–25 | Matches average daily read/write concurrency for shift scheduling data, prevents request queuing caused by exhausted connection pools |
REDIS_URL | redis://default:password@host:6379/1 | Caches frequently queried daily shift scheduling and escalation contact information to reduce database query latency |
Three common mistakes
- Phenomenon: Database connections display "connect ETIMEDOUT" in workflows. Local access to the corresponding data source works, but the connection fails in FastGPT. Cause: The IP addresses of the scheduling system and monitoring alert data sources have not been added to the security whitelist of the environment where FastGPT is deployed, or the ports specified in the configured
PG_URLandREDIS_URLare not open. - Phenomenon: When using FastGPT v4.17.0 in the same workflow, database connection latency is significantly higher than in older versions. Cause: The
DB_MAX_LINKconfiguration is too low, leading to request queuing due to exhausted connection pools, or incremental synchronization is not configured, resulting in full shift scheduling data being loaded on every query. - Phenomenon: Duplicate shift records appear, and shift conflict alerts are not triggered. Cause: A unique constraint has not been added to the combined field of shift date and on-duty personnel in the database corresponding to
PG_URL, or the scheduled conflict verification task is not enabled.
How to confirm the configuration is correct
- Log in to the FastGPT database configuration page, test the connectivity of
MONGODB_URI,PG_URL, andREDIS_URL, and check the returned connection success prompt. - Call the test interface to query shift schedule data, confirm that the returned fields match the preset structure of shift schedules and handover records, with no missing or abnormal fields.
- Simulate multiple concurrent shift scheduling query requests, observe the connection pool usage, and confirm that the number of connections does not exceed the configured threshold of
DB_MAX_LINK. - Check the running logs of FastGPT and associated databases, confirm there are no frequent connection timeout, connection exhaustion, or data synchronization failure error messages.
The values provided 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.