What the data for this category looks like
Warehouse and logistics ledger data primarily comes from inbound, outbound, inventory counting, and transportation scheduling modules in the WMS system. Updates are triggered by business actions. New records are generated every few seconds during high-frequency periods, and updated several times per day during low-frequency periods. Each ledger document includes fields such as material code, batch number, inbound/outbound quantity, storage location, operation time, and operator identifier. Units include pieces, boxes, tons, cubic meters, and others. Time fields use ISO 8601 format. Some associated fields reference basic data from external suppliers or carriers.
What constraints these characteristics impose on database and operations maintenance
High-frequency real-time updated ledger data requires the database connection pool to adapt to sudden traffic, preventing service interruptions caused by connection exhaustion. The multi-field associated document structure requires building composite indexes for frequently queried fields such as material code, batch number, and operation time to reduce query latency. Cross-module associated external data references require the database to support cross-source data synchronization, with regular verification of associated field consistency required. Unit differences across different business scenarios require configuring unified unit conversion rules during queries to avoid statistical result deviations.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://wms_user:secure_pass@db-host:27017/wms_ledger?replicaSet=wms_rs | Adapts to document storage needs for warehouse and logistics ledgers, specifies a dedicated business database name and enables a replica set to improve high availability |
DB_MAX_LINK | 20–30 | Handles concurrent connection requests from high-frequency inbound and outbound operations, prevents connection pool exhaustion from affecting workflow execution |
REDIS_URL | redis://:redis_auth@redis-host:6379/0 | Caches frequently queried ledger statistics results, reducing pressure from direct database access |
PG_URL | postgresql://basic_user:pg_secure@pg-host:5432/wms_basic?sslmode=require | Stores structured data such as basic materials and suppliers, enables SSL to ensure transmission security |
| Database connection timeout | 30 seconds | Matches response expectations for warehouse and logistics businesses, prevents overall workflow slowdowns from overly long timeouts |
Three common configuration mistakes
- Symptom: A "connect ETIMEDOUT" error appears in the database connection step of a workflow, but the database can be accessed normally locally. Cause: The database access whitelist is not configured, or the outbound port of the FastGPT deployment environment is not open to the database service port.
- Symptom: MongoDB logs cannot distinguish connection requests for warehouse and logistics ledger business from other business requests. Cause: A dedicated business database name is not specified in
MONGODB_URI, or connection identifier parameters for the application side are not configured. - Symptom: Workflow execution time increases significantly compared to older versions when using the new FastGPT database connection plugin. Cause: The
DB_MAX_LINKconfiguration is not adjusted, insufficient connection pool leads to frequent connection creation and destruction, increasing execution time.
How to confirm the configuration is correct
- Run a test workflow, call the database connection plugin, and check if returned results include expected warehouse ledger fields such as material code and storage location.
- Check the database monitoring panel to confirm real-time connection counts do not exceed the
DB_MAX_LINKconfiguration value. - Review MongoDB logs to confirm business connection identifiers match the database name specified in the configured
MONGODB_URI. - Simulate multiple concurrent workflow calls to verify no timeout errors occur.
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 2026-09-28.