What this category of data includes
Data sources for this category include change management systems, CI pipelines, business monitoring data, and business calendars. Update frequency is either weekly or after a single change is completed. Daily generated documents include change request forms, risk assessment reports, release window scheduling tables, and rollback plan documents. Data fields include change subject information, risk rating levels, effective time windows, rollback trigger thresholds, and more. All data uses structured or semi-structured formats. This data supports the full process of online troubleshooting and post-incident review.
What constraints these characteristics impose on deployment and upgrade
Since data sources cover multiple independent systems, cross-system permission verification and data synchronization rules must be configured during deployment. This ensures change requests, monitoring data, and other information can be properly pulled and stored. Since update frequency aligns with single changes or weekly cycles, upgrade operations must match preset change window periods. This avoids executing upgrades during business peaks, which introduces additional risk. Since daily documents include multiple types of structured content, storage paths and retrieval indexes must be configured for corresponding documents during deployment. This supports quick retrieval during risk rating steps. Since rollback condition confirmation is a core time-consuming step, quick configurations for rollback triggers must be preset during deployment. This shortens fault response time.
How to set these configurations
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale for this Value |
|---|---|---|
PG_URL | postgresql://username:password@host:5432/fastgpt?sslmode=require | Core database storing structured documents such as change requests and risk assessments. SSL encryption must be configured to protect data security |
REDIS_URL | redis://:password@host:6379/0 | Caches high-frequency access data such as release window scheduling and approval status. Use the default database 0 to avoid conflicts with other businesses |
DB_MAX_LINK | 20–30 connections | Matches the concurrent demand for parallel pulling of multiple documents during a single change process. Prevents database connection exhaustion |
STORAGE_S3_ENDPOINT | Set based on actual testing | Stores unstructured data such as rollback plans and change logs. Must align with the storage region of the deployment environment |
FE_DOMAIN | https://your-fastgpt-domain.com | Configures the front-end access domain name. Used to verify the legitimacy of cross-domain requests, ensuring normal communication between front-end and back-end services for the change process |
Three common configuration errors
- Running the upgrade command returns a
connection refusederror. This occurs whenPG_URLorREDIS_URLis not configured correctly, preventing a successful connection to the database and cache services. - Local deployment results in system response lag, with consistently high memory usage. This occurs when
DB_MAX_LINKis not adjusted, leading to excessive concurrent connections that consume system resources. - Unable to initiate AI conversations after migrating deployment. This occurs when
FE_DOMAINis not configured, causing domain verification failures between front-end and back-end services.
How to verify successful configuration
- Run a database connection test command to verify that the
PG_URLandREDIS_URLconfigurations can establish a normal connection. - Upload a simulated change log file to confirm that the storage service configured via
STORAGE_S3_ENDPOINTcan complete upload and download operations normally. - Submit a simulated change request to verify that the concurrent requests configured via
DB_MAX_LINKcan be processed normally, with no connection timeout errors. - Access the front-end page and initiate a change request process to confirm that the domain configured via
FE_DOMAINmatches the access address, and that requests can be initiated normally.
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.