What data for this category looks like
Common data sources include GitHub or Gitee Issues, release logs, user environment information, and code repositories. Update frequency is daily or weekly. Daily maintenance documents include Issue templates, tag rules, response records, and problem reproduction instructions. Typical users are open source maintainers, community operators, and core contributors. Data fields include Issue number, tags, priority, reproduction steps, associated code snippets, response time, and more. There are no fixed uniform units, as units vary based on field type.
What constraints these characteristics impose on the database and operations link
Data sources are scattered and include both structured and unstructured content, so storage support for both relational and document databases is required. Daily or weekly update frequency requires support for incremental synchronization and batch import, to avoid performance loss from full scans. The core Issue triage link relies on fast retrieval of fields such as tags and priority, so indexes must be created for high-frequency query fields. The most time-consuming steps of problem classification and completing reproduction information require database support for associated queries and text retrieval. Error consequences include problem backlogs and user churn, so databases must have high availability and data backup mechanisms. Unlike Pull Request reviews, this workflow prioritizes problem descriptions and priority, focuses on the problem itself, and does not involve code change-related content.
Configuration Settings
This configuration applies to FastGPT v4.17.0. Adjust values based on actual deployed server resources and data volume.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| PG database connection address | postgresql://username:password@host:5432/issue_operation | Stores structured relational data such as Issue tag rules, response records, and priority mappings |
| MongoDB connection address | mongodb://username:password@host:27017/issue_db | Stores unstructured document data such as Issue descriptions, reproduction instructions, and user environment information |
| Maximum database connections | 20–30 | Balances connection pool resource usage and concurrent processing capacity, calibrated based on actual testing |
| Redis cache address | redis://:password@host:6379/0 | Caches frequently accessed tag rules and Issue priority mappings to reduce database query pressure |
| Incremental sync interval | 600 seconds | Matches daily or weekly data update frequencies, avoids frequent syncs that consume system resources |
Three Common Misconfigurations
- Symptom: Issue retrieval response times out, returns status code 504. Cause: Redis cache for high-frequency tag rules is not configured, so every retrieval directly queries the database, exceeding connection pool limits.
- Symptom: Connection drop errors occur when batch importing historical Issue data. Cause: A reasonable maximum database connection count is not set, concurrent write requests exceed database carrying capacity.
- Symptom: Some Issue tag fields are empty. Cause: Required fields in Issue templates are not validated, leading to dirty data being written to the database and reducing subsequent triage efficiency.
How to Verify Successful Configuration
- Run the built-in database connectivity test script to verify connections to the PG database, MongoDB, and Redis.
- Submit a test Issue, fill in complete tags, reproduction steps, and other information, then check if relevant data is correctly stored in the corresponding database tables or collections.
- Simulate high-frequency retrieval operations, view Redis cache hit logs to confirm that high-frequency data has been correctly cached.
- After adjusting the maximum database connections parameter, monitor connection count metrics during concurrent processing to confirm the parameter takes effect.
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.