What Data for This Category Looks Like
Data for this category comes from data asset inventories, database metadata, business system descriptions, and compliance regulatory documents. Updates occur quarterly or after each business system change. Core documents include data catalogs, classification and grading rules, important data identification tables, and review minutes. Fields include data asset identifiers, classification levels, sensitivity levels, associated business systems, and more. There is no unified fixed unit. Values adjust based on the specific attributes of the data asset.
Constraints Imposed on Deployment and Upgrade
Data sources for this category are scattered. Updates follow no fixed cycle. During deployment, add support for synchronized reading of multi-source metadata. This prevents classification and grading failures caused by delayed data asset inventory results. Document structures are closely linked. They include multiple file types such as data catalogs and classification rules. During deployment, configure import and export logic compatible with linked documents. This prevents configuration breaks. During upgrades, reserve a data verification window. This ensures compatibility between old version classification rules and the newly deployed version. Pause temporary ticket processing during upgrades. This prevents ticket matching errors caused by rule changes.
How to Set Configurations
All configurations below are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | This category has multiple data sources. Support for simultaneous reading of database metadata, classification rule documents, and other data types is required to avoid database connection pool exhaustion. |
MONGODB_URI | Connection address pointing to an independent compliant storage cluster | Classification and grading rules and review minutes must be stored in a compliant database to ensure data access can be audited. |
REDIS_URL | Address of a local cache instance | Used to cache frequently accessed classification rules and data catalogs. This reduces repeated query latency in operations on duty scenarios. |
STORAGE_S3_ENDPOINT | Endpoint pointing to the enterprise's internal compliant storage service | Used to store sensitive documents such as important data identification tables. This complies with storage compliance requirements for data security classification and grading. |
FILE_TOKEN_KEY | Generated per the enterprise's internal document access rules | Used to verify access permissions for sensitive documents in storage. This ensures only authorized personnel can read classification rules. |
Three Common Misconfigurations
- Symptom: The workflow code run node returns a "file read failed" error when executing data classification verification. Cause: The
FILE_TOKEN_KEYparameter is not configured, so access permissions for classification rule documents in storage cannot be obtained. - Symptom: Local Docker deployment instances experience connection timeout and return status code 503 when processing internal tickets. Cause: The
DB_MAX_LINKvalue is lower than the actual number of concurrent requests, which exhausts the database connection pool. - Symptom: Existing review minutes cannot be linked to classification rules after an upgrade. Cause: Batch migration of linked documents was not performed during the upgrade, which causes broken configuration links.
How to Verify Successful Configuration
- Run a test ticket to trigger the data classification and grading process. Check that returned results match preset classification rules.
- View the storage monitoring panel. Confirm that the storage service configured via
STORAGE_S3_ENDPOINTcan read and write classification rule documents normally. - Check database connection logs. Confirm that the connection pool configured via
DB_MAX_LINKhas not been exhausted. - Submit a ticket after a business system change. Verify that updated classification rules can normally match corresponding data assets.
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 2026-10-19.