What this category of data looks like
Data sources include regulatory standards, online environmental monitoring equipment, gas detectors, personnel qualification files, equipment isolation lists, and supervision platforms. Daily documents cover risk identification records, work tickets for hot work, confined space work, lifting operations and other types of work, environmental monitoring records, hazardous waste ledgers, emission monitoring data, and accident and hidden danger rectification reports. Corresponding documents are generated after each operation is completed. Monitoring data is updated in real time or as required by regulations. Qualification and list data are checked and updated on a regular basis. Document fields include key information such as operation type, isolated equipment number, gas concentration value, personnel qualification number, and monitoring timestamp.
Constraints During Deployment and Upgrade
Since data sources include multiple types of equipment, files and supervision platforms, deployment must support adaptive configuration for multi-source data access. Different data have significantly different update cadences. Real-time monitoring data requires a low-latency synchronization link during deployment. Qualification and list data updated periodically can use batch synchronization tasks. There are diverse document types and structures. Upgrades must support parsing rules and field extraction for different documents. EHS data has high compliance requirements. Deployment must configure corresponding verification logic to ensure data meets regulatory requirements. Fluctuations in operation frequency lead to changes in data volume. Upgrades must reserve elastic computing and storage resources to support peak loads.
Configuration Guidelines
This configuration guide applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–200 connections | The operation and monitoring data volume of manufacturing enterprise EHS departments fluctuates greatly. This parameter controls the maximum number of connections in the database connection pool to adapt to peak loads |
MONGODB_URI | Configure according to the enterprise's internal MongoDB cluster address | Unstructured documents such as work tickets and hidden danger rectification reports need to be stored in MongoDB, and must be connected to the enterprise's existing storage cluster |
REDIS_URL | Enterprise internal Redis instance address on port 6379 | Real-time monitoring data and personnel qualification verification results need to be cached to reduce repeated query latency |
STORAGE_S3_ENDPOINT | Access endpoint of the enterprise object storage service | Large-volume files such as hazardous waste ledgers and emission monitoring data need to be stored in the enterprise's own object storage to ensure data controllability |
FILE_TOKEN_KEY | 32-character random string | Download links of sensitive documents such as work tickets and monitoring records need to be encrypted to prevent unauthorized access |
ROOT_KEY | Configure according to enterprise permission management requirements | The access scope of the platform's highest permissions must be controlled to comply with the security and compliance requirements of EHS data |
Three Common Configuration Mistakes
- Symptom: Conversation response timeout, logs show database connection timeout. Cause: The
DB_MAX_LINKparameter is not configured, or the value is set too low, which cannot support multi-operation data query requests during peak hours. - Symptom: 404 error returned when accessing enterprise online monitoring equipment. Cause: The
STORAGE_S3_ENDPOINTorREDIS_URLparameter is not configured correctly, causing the data synchronization link to be interrupted and unable to pull monitoring data normally. - Symptom: Missing fields after work ticket documents are parsed. Cause: The special structure of this category of documents is not adapted, and the corresponding field extraction rules are not configured, resulting in failure to correctly extract key information such as risk identification records and operation time.
How to Confirm Successful Configuration
- Log in to the FastGPT backend, check the database connection pool status, and confirm that the configured value of the
DB_MAX_LINKparameter matches the actual runtime connection count. - Upload a hot work ticket document to test whether the parsed result includes key fields such as operation type and guardian qualification number.
- Initiate a real-time monitoring data synchronization request to confirm that data can be pulled normally and stored in the corresponding storage location.
- Generate a download link for a hazardous waste ledger document to test whether the link can be accessed normally and has no unauthorized access risks.
The values provided here are common starting points and should be measured against the reader's own samples.