What the data for this category looks like
Ready-mixed concrete production business data comes from commercial concrete batching plant control systems, project laboratories, raw material inspection ledgers, and engineering order systems. Daily generated documents include mix design notices, opening identification records, production and delivery slips, aggregate, cement and admixture inspection reports, moisture content measurement records, test block strength reports, and more. Fields include aggregate type, real-time moisture content, mixing duration, pouring location, curing age, and others.
Data update frequency follows per vehicle production batch, per batch of incoming raw materials, and daily laboratory inspection cycles. Core time-consuming steps include adjusting water and batching quantities based on real-time aggregate moisture content, coordinating production, transportation and site pouring windows, tracking test block strength, and handling abnormal results.
What constraints do these characteristics impose on deployment and upgrades
This category has high-frequency data updates and scattered data sources. Deployment requires adaptation to multi-system interface integration and real-time data synchronization. Document types include structured reports and unstructured text. Support must be provided for loading process specifications and standard files in different formats.
Since production data directly relates to engineering quality, the deployment environment must be limited to the batching plant's internal local area network to avoid external access risks. Upgrade links must ensure no interruption to production data, must not affect ongoing batching and transportation processes, and must support migration of historical test block records and mix proportion data. This prevents business data loss or format confusion caused by version updates.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–200 connections | Adapt to concurrent query demands for frequently accessed business documents such as mix design notices and test block records |
REDIS_URL | Local 6379 port instance | Cache real-time aggregate moisture content and production progress data to reduce database query pressure |
STORAGE_S3_ENDPOINT | Configured according to local object storage nodes | Store large-volume business documents such as raw material inspection reports and test block strength reports |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Protect download permissions for process specification files and prevent unauthorized access to internal documents |
FE_DOMAIN | Batching plant internal local area network domain name | Limit service access scope and ensure internal use security of production data |
Three common mistakes
- Symptom:
docker buildreports directory not found, error message includesERROR: failed to solve: failed to comput. Cause: The build context does not include business document directories such as mix design notices and raw material inspection documents, and local data volumes are not correctly mounted to the document reading path inside the container. - Symptom: After sending an HTTP request to upload a TXT-format process specification file, the backend returns an empty result or format error. Cause:
FILE_TOKEN_KEYis not correctly configured, causing file permission verification to fail and preventing reading of the uploaded local TXT file. - Symptom: Slow operation after local deployment, with high internal access latency. Cause: The local cache instance configured via
REDIS_URLis not used, and production data is directly queried from the database during high-frequency queries, causing request backlog.
How to confirm the configuration is correct
- Run the
docker pscommand to confirm that all FastGPT v4.17.0 service containers are in running status with no abnormal exit records. - Send an internal HTTP request to upload a test mix design notice TXT file, and verify that the backend correctly returns a TXT-format processed file containing strength check results.
- View the monitoring metrics corresponding to
REDIS_URLto confirm that the cache hit rate is in a reasonable range, with no sharp increase in database requests caused by a large number of cache misses. - Adjust the
DB_MAX_LINKparameter to 150 connections, then verify that no connection timeout errors occur when more than 3 internal users simultaneously query process specifications.
The values given are common starting points and should be measured against the reader's own samples.