What the data for this category looks like
Core data for this category comes from meteorological early warning systems, hydrological monitoring systems, emergency command platforms, grassroots disaster reporting systems, and video surveillance. Daily generated documents include duty logs, early warning notices, consultation minutes, rapid disaster reports, emergency response plans, and material transfer orders. Typical document structures include fields such as time, location, quantitative rainfall and water level data, personnel and material information, and response progress. Common units include millimeters, cubic meters, number of people, tons, and others. Data updates occur daily. In some real-time response scenarios, the update interval shortens to minute-level.
What constraints these characteristics impose on deployment and upgrade
This category has scattered data sources, fields with large amounts of quantitative information, and a mix of daily and real-time update rhythms. These factors create multiple constraints for deployment and upgrade. Multi-source data access requires preconfiguring cross-system docking parameters during deployment to avoid data synchronization interruptions. Structured fields and specific units require storage configurations optimized for long text and precise matching rules. During upgrades, retain the old field mapping logic. High-frequency updates and real-time scenarios require adjusting database connection pool and cache parameters to maintain read and write performance. Configure a gray release process to prevent upgrades from disrupting emergency duty operations.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PG_URL | postgresql://username:password@host:5432/fastgpt?sslmode=disable | Stores structured documents such as duty logs and rapid disaster reports, and supports efficient querying and updating of relational data |
REDIS_URL | redis://:password@host:6379/0 | Caches frequently accessed rainfall and water level data to reduce database read and write pressure |
DB_MAX_LINK | 20–30 | Adapts to daily high volumes of document generation and data synchronization requests, preventing database connection exhaustion |
STORAGE_S3_ENDPOINT | Fill in according to the cloud storage endpoint of the deployment environment | Stores unstructured documents such as early warning notices and consultation minutes, ensuring data persistence |
ROOT_KEY | Randomly generated 32-bit string | Configures the system's highest privilege access key to ensure operational security after deployment |
FE_DOMAIN | https://your-fastgpt-domain.com | Configures the frontend access domain name, adapting to internal access requirements for emergency duty scenarios |
Three common mistakes
- Deploying only the Milvus storage solution without configuring a relational database results in inefficient querying of structured data such as duty logs and rapid disaster reports. This occurs because the high proportion of structured documents in this category is not considered, and a single storage solution is incorrectly selected.
- Failing to adjust the
DB_MAX_LINKparameter during deployment causes database connection timeout errors during peak early warning release periods in flood season. This occurs because the high-frequency data update scenario of this category is not addressed, and the default connection count configuration is used. - Failing to retrieve the userId field after system upgrade leads to user identity verification failures and inability to generate emergency documents normally. This occurs because the old version userId mapping logic is not retained, and new identity verification rules are directly substituted.
How to confirm the configuration is successful
- Access the configured
FE_DOMAIN, log in to the system, and attempt to retrieve emergency document templates and real-time data related to meteorological and hydrological conditions to confirm normal data loading. - Submit a simulated duty log or rapid disaster report document, check whether the database can store the document normally and complete basic queries, and verify that the
PG_URLconfiguration takes effect. - Verify the storage service corresponding to
STORAGE_S3_ENDPOINT, confirm that the upload and download processes for unstructured documents such as early warning notices and consultation minutes operate correctly. - Use the configured
ROOT_KEYto call internal system interfaces, confirm that the highest privilege access logic functions correctly.
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 2026-09-28.