What this category of data looks like
This category of data comes from multiple sources including regulatory standards, online environmental monitoring equipment, gas detectors, personnel qualification files, equipment isolation lists, supervision platforms, and more. Daily documents include risk identification records, work tickets such as hot work, confined space, and lifting work, monitoring records, hazardous waste ledgers, emission monitoring data, accident and hidden danger rectification reports. Data updates are triggered upon completion of individual work, real-time monitoring requirements, or regular inspections. Fields include work identifiers, monitoring parameters, personnel qualification numbers, compliance status, and more. This requires adaptation to structured and unstructured data types across multiple formats.
What constraints do these characteristics impose during deployment and upgrade
Multi-source heterogeneous data sources require that access adaptation rules for multiple types of data sources be configured during the deployment phase, to support data synchronization from device APIs, scanned paper documents, and supervision platform interfaces. Coexistence of high-frequency real-time updated monitoring data and periodically updated ledger data requires targeted configuration of synchronization task trigger frequencies and caching strategies. Documents with fixed field structures covering multiple business scenarios require precise field mapping rules to be configured during deployment, to ensure accurate compliance verification during ledger summary. Security and compliance attributes require that the upgrade phase be compatible with the format and permission policies of existing ledgers, to prevent historical data from becoming unqueryable or permissions from expiring due to version updates. FastGPT v4.17.0 optimizes the compatibility configuration for multi-source data synchronization for this scenario; pay attention to version adaptation.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@[host address]:[port]/fastgpt_safety?authSource=admin | Stores structured documents such as work tickets and hazardous waste ledgers, requires persistence and support for multi-document associated queries |
REDIS_URL | redis://:[password]@[host address]:[port]/0 | Caches real-time monitoring data and personnel qualification verification results to reduce repeated query latency |
STORAGE_S3_ENDPOINT | http://192.168.1.100:9000 (configure according to the enterprise's own storage service) | Stores scanned work tickets and original emission monitoring data to meet compliance retention requirements |
DB_MAX_LINK | 20–30 | This category has multiple data sources and frequent updates, to avoid connection pool exhaustion affecting real-time data synchronization |
ROOT_KEY | Random string of 16 or more characters | Highest permission configuration for the management platform, to prevent unauthorized access to compliance-sensitive data |
FILE_TOKEN_KEY | 32-bit random string | Encrypts file upload and download tokens to prevent unauthorized access to ledger files |
Three Common Configuration Errors
- Symptom: A database connection failure prompt appears after service startup. Cause: The database name configured in
MONGODB_URIdoes not match the actual deployed database name, or the database port access permission is not enabled. - Symptom: A 404 error is returned when calling the ledger query interface. Cause:
STORAGE_S3_ENDPOINTis not configured correctly, resulting in failure to read scanned work tickets, or the storage bucket permission configuration is incorrect. - Symptom: Real-time monitoring data cannot be synchronized to the production ledger. Cause: The cache expiration time configured in
REDIS_URLis too short, resulting in loss of intermediate cache data, or the multi-source data synchronization task is not enabled.
How to Confirm Configuration Completion
- Run the built-in database connection test tool in FastGPT to verify that the connection status configured for
MONGODB_URIandREDIS_URLis normal. - Upload a standard scanned hot work ticket, check that the file can be stored normally and accessed through the file management module.
- Submit a simulated confined space work data, confirm that the data can be written to the database and displayed normally in the ledger list.
- Attempt to access the management backend using a key other than
ROOT_KEY, confirm that unauthorized access requests are blocked.
The values provided are common starting points and should be measured against the reader's own samples.