What Data for This Category Looks Like
Data sources for this category include advertising platforms, customer relationship management systems, front-end attribution SDKs, and online form systems. Updates run on a daily or weekly schedule. Daily associated documents include attribution rule configuration tables, lead distribution tables, channel effect reports, and abnormal lead checklists. Data fields include channel identifiers, lead unique identifiers, assigned sales accounts, conversion node times, and more. There are no mandatory unified statistical units; field formats are matched only to business scenarios.
Constraints Imposed by These Characteristics on Deployment and Upgrade
For the deployment and upgrade of FastGPT v4.17.0, since data sources for this category are scattered and involve multiple types of system integrations, connection and synchronization configuration for multiple data sources must be adapted during deployment. The daily or weekly update schedule requires configuring the trigger cycle parameters for scheduled tasks during deployment to avoid synchronization conflicts. Associated structured documents include attribution rules, lead distribution tables, etc., so document parsing logic for different formats must be adapted. Data abnormalities can trigger business disputes, so threshold parameters for data verification and abnormal alerts must be configured during deployment to ensure data accuracy.
How to Set Configuration Values
| Configuration Item | Recommended Value | Rationale for This Setting |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/database?authSource=admin | Core storage for integrating CRM and lead data, must match the storage protocol and permissions of business data |
PG_URL | postgresql://user:pass@host:5432/channel_db?sslmode=require | Stores structured data for attribution rules and channel reports, must adapt to multi-field index requirements |
REDIS_URL | redis://:password@host:6379/0 | Caches real-time attribution data and lead deduplication markers to reduce repeated query overhead |
DB_MAX_LINK | 20–30 | Adapts to concurrent connection requirements for multiple data sources, avoids connection pool exhaustion affecting synchronization tasks |
FE_DOMAIN | https://your-fastgpt-domain.com | Configures the front-end access domain name to ensure normal jump links for internal tickets and reports |
STORAGE_S3_ENDPOINT | Configure according to cloud service provider region | Stores attachments for channel reports and abnormal checklists, must match the access endpoint of the storage service |
Three Common Configuration Errors
- Symptom: Container restarts infinitely after startup, logs show database connection timeout. Cause: Permission parameters for
MONGODB_URIorPG_URLare not configured correctly, resulting in failure to establish a data connection. - Symptom: A large number of duplicate leads appear after channel data synchronization. Cause:
REDIS_URLis not configured to cache lead deduplication markers, or the scheduled synchronization cycle is set too short, leading to repeated pulls. - Symptom: Internal tickets cannot jump to the channel report page normally. Cause:
FE_DOMAINis configured incorrectly, resulting in failed front-end jump links.
How to Verify Successful Configuration
- Run the built-in database connectivity test tool to verify the connectivity of
MONGODB_URIandPG_URL, and confirm there are no permission or address configuration errors. - Trigger a manual data synchronization task, compare the number of synchronized data entries with the stock data of the source system, and confirm the synchronization logic is working normally.
- Submit a test internal ticket, check whether the domain name of the ticket jump link matches the
FE_DOMAINconfiguration, and confirm the domain name configuration is effective. - View the connection pool monitoring panel, confirm that the current active connection count does not exceed the
DB_MAX_LINKconfiguration value, and there is no connection exhaustion situation.
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.