What this type of data looks like
Ledger data for steel smelting comes from real-time collection sensors of equipment such as blast furnaces, converters, and continuous casters, batching control systems, finished product inspection reports, equipment operation and maintenance logs, and production work order systems.
Update frequencies are divided into three levels: real-time (operating parameters such as furnace temperature, air pressure, feeding speed, updated once per second), shift (data such as shift feeding volume and molten steel output weight, updated once per shift), and batch (ledgers including temperature curves and composition changes for a single furnace’s full smelting process, updated once per furnace).
The document structure includes smelting batch number, furnace body number, collection time, process parameters, feeding ratio, finished product composition indicators, equipment operating duration, and associated production work order ID. Fields include numerical values with units, timestamps accurate to the second, and no redundant duplicate fields.
What constraints do these characteristics impose on the database and operations link
Reference only; verify against the target FastGPT release and deployment documentation.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PG_URL | postgresql://fastgpt:securepass@db-host:5432/steel_smelting?sslmode=require | Stores structured ledger data and associated business indexes, complies with database specifications for FastGPT v4.17.0, specifies the corresponding business database, enables SSL to secure internal network data transmission |
MONGODB_URI | mongodb://fastgpt:securepass@mongo-host:27017/steel_smelting?authSource=admin&maxPoolSize=60 | Stores unstructured inspection reports and equipment logs, sets connection pool size to adapt to high-frequency write requirements, meets connection configuration requirements for FastGPT v4.17.0 |
DB_MAX_LINK | 60–100 | Adapts to concurrent connection requirements for real-time data collection and batch aggregation, avoids service blocking caused by exhausted connections |
REDIS_URL | redis://:securepass@redis-host:6379/1?maxmemory-policy=allkeys-lru | Caches batch aggregation results of high-frequency queries to reduce repeated calculation overhead for databases, complies with cache configuration rules for FastGPT v4.17.0 |
Three common mistakes
- Phenomenon: Local code debugging works normally, but a database connection timeout error with status code 503 is prompted after packaging as a Docker image. Cause: Database configuration parameters such as
PG_URLwere not correctly injected during image construction, causing the application inside the container to fail to read database connection information from the production environment. - Phenomenon: An error
column vector does not existis prompted after startup, and the ledger vector retrieval function cannot be loaded. Cause: The PostgreSQL vector extension was not initialized correctly, or the step of creating vector fields was missed when executing database migration scripts. - Phenomenon: The FastGPT instance deployed on Sealos cannot fully export ledger data, and some batch records are missing from the backup file. Cause: An incremental backup strategy was not used, and when only full backups were performed, database tables were not locked, causing new write data generated during the backup process to not be included.
How to confirm configurations are correct
- Execute the database connection test script to verify the connectivity of the
PG_URLandMONGODB_URIconfigurations, and confirm there are no authentication or address errors. - Check the database connection pool monitoring to confirm that the current number of connections does not exceed the upper limit set by
DB_MAX_LINK, and there is no connection overflow. - Trigger a ledger aggregation task, check whether the corresponding batch aggregation result is generated in the Redis cache, and confirm that the
REDIS_URLconfiguration takes effect. - Perform a manual backup operation to verify that the backup file contains complete smelting batch data with no missing items.
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.