What the data for this category looks like
Core data for grain reserve comes from grain depot daily operation ledgers, warehouse inspection records, employee scheduling systems, and inventory monitoring equipment. Data update cycles cover real-time (inbound and outbound operations), daily (inspection submissions), and weekly (scheduling adjustments). The data includes structured tabular data. Fields include grain variety, storage bin number, moisture content, inbound and outbound quantity, with units of tons, kilograms, and percentage. It also includes unstructured inspection photos and video files.
What constraints these characteristics impose on deployment and upgrades
Structured ledger data has many fields with close associations. Deployment requires configuring storage components that support multi-table associations. Unstructured inspection files have large sizes. Upgrades require expanding available storage node space. Real-time inbound and outbound data requires stable database connection performance. Deployment must verify database read/write latency. Employee service scenarios require integration with internal office systems. Upgrades must reserve interface compatibility configuration space to avoid interrupting daily office workflows. Additionally, grain reserve data compliance requirements mean deployment environments must meet internal security standards. Upgrade operations must back up core ledger data in advance.
How to set configurations
| Config Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Grain reserve data includes multi-dimensional associated ledgers and real-time inventory, requiring sufficient database connections to support daily concurrent read/write operations |
STORAGE_S3_ENDPOINT | Exclusive access address for intranet object storage | Unstructured inspection files and documents have large sizes; intranet deployment reduces transmission latency and ensures access stability |
REDIS_URL | Exclusive intranet Redis instance address | Real-time inventory data and employee session information need to be cached to ensure low-latency access and session persistence |
MONGODB_URI | Database connection address corresponding to grain depot operation ledgers | Stores non-fixed-structure ledger data with multiple associated fields, adapting to business expansion needs |
FE_DOMAIN | Exclusive secondary domain name of the internal office system | Used to generate permissioned file access links, adapting to the secure access scenario of internal employee services |
Three common errors
- Phenomenon: Docker containers fail to start during deployment in an Alibaba Cloud intranet environment. Logs display image pull timeout errors. Cause: No intranet image source is configured. Using public network pull leads to cross-network connection failure.
- Phenomenon: When importing Excel grain depot ledgers, some custom fields (such as bin number, moisture content) are parsed as empty. Cause: The system does not adapt to exclusive grain reserve ledger fields. The default import template does not match corresponding column names.
- Phenomenon: Real-time inventory query responses time out. Background logs show database connection exhaustion. Cause: The
DB_MAX_LINKconfiguration value is too low. Concurrent read/write requests exceed the database connection limit.
How to confirm the configuration is complete
- Run the database connection test tool included with FastGPT v4.17.0 to verify that the configured connection count can support daily concurrent read/write requirements.
- Upload a single 100MB inspection video file to confirm normal storage and generation of a valid internal access link.
- Import a standard Excel ledger containing grain variety and storage bin number fields to confirm all custom fields can be parsed and stored normally.
- Initiate multiple rounds of internal employee service sessions to confirm cached session information can be read and updated normally.
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.