What data for this category looks like
Data for this category typically originates from customer ITSM systems, infrastructure monitoring platforms, asset inventory ledgers, and on-duty shift logs. Daily generated documents include on-site daily reports, helpdesk tickets, monthly inspection reports, and SLA compliance monthly reports. Data updates occur primarily on a daily basis, with some summary reports updated monthly. Common data fields include ticket numbers, inspection nodes, service response times, asset numbers, and others. There is no unified mandatory format, and adaptation to the customer’s existing IT management system is required.
What constraints these characteristics impose on deployment and upgrade
Deployments for this category must adapt to the customer’s existing IT management system, so generic deployment scripts cannot be used directly. Customer ITSM permission interfaces must be connected in advance to ensure compliant data synchronization. Since data sources are scattered and formats are inconsistent, multi-source data access adaptation modules must be configured during the deployment phase to avoid index failures caused by mismatched data fields. Deployments for on-site services must be completed at the customer’s location. Upgrade operations must avoid peak business hours, and existing customer operation data must be backed up in advance to prevent loss of core business data such as on-site daily reports and ticket records. Additionally, since the service relies on the customer’s existing database and caching services, parameter configurations matching the customer’s environment must be strictly used during deployment to avoid connection exceptions.
How to configure settings
These configurations are adapted for FastGPT v4.17.0, and should be adjusted based on the customer’s on-site environment:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Adapts to concurrent access demands for daily tickets and inspection data of on-site services, preventing database connection exhaustion |
PG_URL | postgresql://[username]:[password]@[customer database address]:5432/[customer operations database name] | Connects to the customer’s existing PostgreSQL database to store business data such as tickets and inspection reports, adapting to the customer’s IT management system |
REDIS_URL | redis://:[password]@[customer cache address]:6379/0 | Caches real-time status of on-site tickets and inspection data to reduce database access pressure |
STORAGE_S3_ENDPOINT | Fill in according to the customer’s object storage service address | Adapts to the customer’s existing storage system for storing document resources such as on-site daily reports and inspection attachments |
ROOT_KEY | Generate a random string in accordance with customer security specifications | Meets the customer’s security management requirements for platform access permissions, preventing unauthorized access |
FE_DOMAIN | Fill in the access domain name specified by the customer | Adapts to the customer’s internal network environment, ensuring on-site engineers can access the platform via the internal domain name |
Three common mistakes
- Symptom: Knowledge base index cannot be created after deployment, with logs indicating core fields are empty. Cause: The format of tickets exported from the customer’s ITSM was not adapted, and field mapping rules for multi-source data were not configured, resulting in missing key information required for indexing.
- Symptom: AI model calls return connection timeout or path errors. Cause: The
/v1path was not added at the end of the model API address, causing requests to fail to route correctly to the target service. - Symptom: Historical on-site daily reports cannot be exported normally after upgrade. Cause: Existing historical documents stored by the customer were not backed up in advance, and the storage configuration was overwritten during the upgrade process, making original business resources inaccessible.
How to confirm successful configuration
- Run a database connection test to verify connectivity of configurations such as
PG_URLandREDIS_URL, confirming no connection timeout or permission errors. - Import a single on-site ticket data entry, check the index generation status, and confirm field matching with no missing information.
- Configure a test model API address and send a request to verify that the call chain operates normally, confirming the path configuration is compliant.
- Trigger an upgrade rollback test to verify that backup data can be restored normally, ensuring that upgrade operations will not cause loss of core business data.
The values provided are common starting points and should be evaluated against the reader’s own operational 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.