What this category of data looks like
Data for this category flows through the full lifecycle of software functional defects. Sources include internal defect management systems, version iteration test reports, code commit records, and end-user feedback. Daily produced documents include standardized defect tickets, version regression verification checklists, repair verification records, and defect statistical reports. Data updates are triggered by daily incremental updates or per version iteration. Core fields include defect ID, priority, reproduction steps, verification status, and associated code commit ID. No non-standard units are used.
What constraints do these characteristics impose on the deployment and upgrade phase
Data sources for this category are scattered. The deployment phase must reserve extended configurations to adapt to multiple data source types, to avoid adaptation issues when connecting to different defect management systems. Data update rhythm fluctuates greatly. Adjustable incremental synchronization cycles must be configured to avoid excessive server resource usage from full data pulls. Core document structures are fixed. Parsing templates for corresponding fields must be preset during deployment, to ensure that fields in documents such as defect tickets and regression checklists can be correctly identified by the system. High-priority defect processing timeliness requirements are strict. Priority alert trigger rules must be configured during deployment, to ensure that internal tickets are promptly routed to the corresponding handlers.
How to configure settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 concurrent connections | Adapts to concurrent pull requirements for multiple data sources including defect management systems and test reports, avoids connection pool resource exhaustion |
MONGODB_URI | Local high-availability cluster connection string | Stores unstructured documents such as defect tickets and regression checklists, meets high-frequency read and write storage requirements |
REDIS_URL | Local port 6379 instance | Caches high-frequency data such as defect priority rules and ticket routing status, reduces database query latency |
STORAGE_S3_ENDPOINT | Local object storage endpoint | Stores files such as defect reproduction screenshots and test report attachments, unifies management of static resources during deployment |
ROOT_KEY | Randomly generated 32-bit secret key | Configures system administrator access permissions, prevents unauthorized modification of core defect synchronization configurations |
FILE_TOKEN_KEY | Signature key with a 24-hour validity period | Used to generate access tokens for defect attachments, controls file access permissions for internal tickets |
Three common misconfigurations
- Phenomenon: After startup, ticket data from the defect management system cannot be pulled, returning a
401 Unauthorizederror. Cause:ROOT_KEYor the access key for the connected system is not configured correctly, leading to failed permission verification. - Phenomenon: Timeout occurs when synchronizing defect data, with a single synchronization taking more than 300 seconds. Cause: The concurrent connection count for
DB_MAX_LINKis not adjusted, leading to connection pool blocking when pulling data from multiple sources. - Phenomenon: Defect reproduction screenshots cannot be displayed normally after upgrade. Cause: The storage configuration for
STORAGE_S3_ENDPOINTis not updated synchronously, leading to inaccessibility of the old storage path.
How to confirm configurations are correct
- Run a database connection test to verify that
MONGODB_URIandREDIS_URLconfigurations can connect normally. - Submit a test defect ticket, check whether the system can synchronize to the internal ticket system according to preset rules, and confirm that defect ticket fields are correctly parsed.
- Upload a test defect reproduction screenshot, verify that the storage path for
STORAGE_S3_ENDPOINTcan be accessed normally. - Check the administrator backend, confirm that the permission verification logic configured via
ROOT_KEYcan properly block unauthorized access.
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.