What This Category’s Data Looks Like
Daily documents for this category include raw milk acceptance records, standardized ingredient lists, pasteurization or UHT heat treatment records, CIP cleaning records, filling records, and sample retention and microbial test reports. Data comes from milk source testing equipment, production MES systems, homogenization and heat treatment online terminals, CIP systems, and LIMS laboratory management platforms. Data syncs in real time per individual milk tank or production batch. Fields include antibiotic detection values, heat treatment temperature and duration, aseptic filling pressure, and microbial colony count, among others. Corresponding units include mg/kg, ℃, seconds, MPa, and CFU/mL.
Constraints During Deployment and Upgrade
This category’s data is scattered and has high real-time requirements. During deployment, multi-source heterogeneous data access must be adapted, and stable synchronization of multiple data sources including milk source testing equipment, MES systems, and device terminals must be ensured. Production batches are closely linked and the production chain is continuous. Precise batch traceability association rules must be configured during deployment. During upgrades, compatibility with legacy data and smooth transition of new functions must be guaranteed. Additionally, field units are diverse. Standardized mapping configuration must be completed in advance to avoid unit mismatch parsing errors during Q&A. A high-availability deployment architecture must be reserved to handle real-time data requests.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Bind the sharded cluster address storing production batch data | This category’s data syncs in real time per batch, and sharded clusters support high-concurrency writes and traceability queries |
REDIS_URL | Configure as an intranet cache node, set cache expiration time to 300 seconds | Caches frequently called heat treatment and CIP process parameters; 300 seconds matches the average production interval per milk tank |
DB_MAX_LINK | 80–120 | Adapts to concurrent connection requirements of multiple source devices and systems, prevents service exceptions caused by exhausted connection pools |
STORAGE_S3_ENDPOINT | Connect to the dedicated address of the enterprise intranet object storage | Ensures secure transmission of sensitive documents such as sample retention reports and raw milk test records, avoids public network exposure |
ROOT_KEY | Randomly generated 32-bit string | Restricts authorized operations only to maintenance personnel, complies with security control requirements for production data |
The configuration values provided are common starting points. They should be validated against local deployment samples.
Three Common Mistakes
- Phenomenon: After performing an online update on a Docker-deployed instance, the system version still displays the legacy version. Cause: The old container was not stopped and the specified version image tag was not mounted, causing the update process to fail to replace the running image files.
- Phenomenon: After pulling the target version image, the background-displayed version number does not match the expected one. Cause: The local image cache was not cleared, and the container loaded the outdated image during startup, causing version matching exceptions.
- Phenomenon: When configuring third-party access, the open platform prompts that the receiving address verification failed. Cause: The service was not deployed on a publicly accessible node, and correct port mapping and domain name resolution were not configured, preventing external systems from calling the service interface.
How to Verify Successful Configuration
- Log in to the system backend, check the data source connection status, and confirm that all configured connection addresses such as
MONGODB_URIandREDIS_URLshow normal status. - Initiate a test query, enter a question related to raw milk acceptance or heat treatment processes, and verify that the returned results include correct document fields and unit matching logic.
- Execute a simulated upgrade process, confirm that the gray release nodes do not affect the Q&A service of the normal production chain.
- Check the permission configuration, confirm that only authorized personnel can access the system backend management interface via
ROOT_KEY.
This configuration guide applies to FastGPT v4.17.0.