What the data for this category looks like
State-owned asset management company ledger data primarily comes from four sources: state-owned asset supervision platforms, internal asset systems, financial accounting systems, and property rights registration archives. Update cycles cover real-time updates for daily asset changes, monthly aggregated ledger updates, and annual final report updates. Most documents are structured two-dimensional tables. They include fields such as asset number, asset category, recorded original value, accumulated depreciation, service life, storage location, ownership status, and disposal date. Supported units include ten thousand yuan, square meters, units/sets, pieces, and other standard units.
What constraints these characteristics impose on deployment and upgrade
These data characteristics create clear constraints for deployment and upgrade workflows. Multi-source data integration requires separate configuration of different database connections. MONGODB_URI and PG_URL must be set separately for state-owned asset supervision and internal financial data sources. High-frequency asset change updates generate database connection pressure. Adjust the value of DB_MAX_LINK to match connection pool capacity. Multiple structured fields and sensitive information are present. Configure REDIS_URL to cache non-sensitive fields from frequent queries, and use ROOT_KEY to encrypt sensitive data. Large annual reports and original ledger files require STORAGE_S3_ENDPOINT configuration for storage. This avoids occupying local disk space.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Matches connection needs for high-frequency ledger data updates, prevents connection pool exhaustion |
MONGODB_URI | Dedicated MongoDB connection string for state-owned asset supervision systems | Stores unstructured change records for asset changes |
PG_URL | Internal financial system PostgreSQL connection string | Stores structured asset value and ownership field data |
REDIS_URL | redis://localhost:6379 | Caches frequently queried asset classification mapping tables, reduces database query pressure |
STORAGE_S3_ENDPOINT | Enterprise internal S3-compatible storage endpoint | Stores large files such as original ledger Excel files and annual report PDF files |
ROOT_KEY | 32-digit randomly generated string | Encrypts access permissions for sensitive asset fields, complies with state-owned asset data security standards |
Three common misconfigurations
- Issue: Docker image pull fails. Configuring a terminal proxy and Alibaba mirror source does not resolve the issue. Cause: A global proxy was not added to the Docker daemon configuration file. Terminal-only proxy configurations do not take effect.
- Issue: Service startup fails with a database connection failure and sandbox component not ready prompt. Cause: Sandbox container startup configuration was omitted. Ledger aggregation requires the sandbox to handle parsing and format conversion for Excel, PDF, and other files.
- Issue: Runtime error occurs on ARM architecture servers, with a prompt about incompatible image architecture. Cause: Official published images only support amd64 architecture, and do not adapt to ARM64 server environments.
How to confirm successful configuration
- Run the
docker pscommand. Verify that all dependent containers including MongoDB, PostgreSQL, Redis, and sandbox are in a running state. - Access the configured frontend domain name. After logging into the system, test connections to the state-owned asset supervision system and financial system data sources. Confirm connection status is normal.
- Upload a monthly ledger Excel file. Check if the system correctly parses fields such as asset number and recorded value, and generates preview content.
- Review background runtime logs. Confirm that no continuous over-limit error messages appear for the
DB_MAX_LINKconfigured connection count.
The values provided here are common starting points. They should be assessed against the specific deployment samples in the target environment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.