What Data Looks Like for This Category
This category of data comes from daily deliverables of internet product teams, business analysts, and product managers. It includes requirement research notes, PRD documents, user story lists, and requirement change tickets. Data is collected from customer interview records, internal ticketing systems, public competitor pages, and user behavior tracking dashboards. Updates occur weekly or per version iteration. Each single document typically has three core fields: business objectives, acceptance criteria, and functional boundaries. There is no unified fixed unit. Content volume is measured using character count or item count only.
Constraints on Database and Operations Workflows
A multi-source mixed data structure requires the database to support storage and retrieval of structured tickets, semi-structured PRDs, and unstructured interview notes. Weekly or version-level update cycles require database connection pool configurations to balance concurrent access and resource usage. This avoids performance loss from frequent connection establishment. High-frequency requirement change synchronization needs require the database to support version rollback and field change log recording. This allows quick identification of the impact scope of requirement adjustments. The strong association between acceptance criteria and boundary conditions requires database fields to support precise matching and range queries. This reduces retrieval errors. Requirement document volume grows with each version iteration, so the database needs horizontally scalable operations capabilities. This prevents storage bottlenecks.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://user:pass@host:27017/prd_db?authSource=admin | Adapts to FastGPT v4.17.0 multi-source unstructured document storage specifications, supports nested field retrieval for research notes and PRDs |
PG_URL | postgresql://user:pass@host:5432/prd_metadata | Stores structured metadata such as requirement change tickets and acceptance criteria, supports complex range and precise matching queries |
DB_MAX_LINK | 20–30 | Matches weekly or version-level update cycles, balances concurrent access and server resource usage, prevents connection exhaustion |
REDIS_URL | redis://:pass@host:6379/0 | Caches frequently accessed requirement document metadata, shortens retrieval response times |
| Connection timeout | 300 seconds | Prevents connection blocking caused by loading large PRD documents, adapts to the maximum character volume of a single document |
| Index shard count | 8–12 | Adapts to retrieval performance requirements for multi-source mixed data, can be flexibly adjusted as document volume grows |
Three Common Misconfigurations
- Phenomenon: A
500 Internal Server Erroris returned when searching for requirement documents. Logs show MongoDB version incompatibility. Cause: The correct MongoDB version was not selected based on the unstructured document storage needs of this category. Using an outdated or overly new version causes field parsing failures. - Phenomenon: A locally Docker-deployed service experiences Redis connection timeout, and cannot load frequently cached PRD metadata. Cause:
REDIS_URLwas not configured as a container address on the same network as MongoDB and PostgreSQL. This causes excessive cross-network access latency. - Phenomenon: The number of results returned when batch searching requirement change tickets is far lower than expected. Cause: Reasonable database index shards were not configured, causing some data to not be properly indexed and unable to match search conditions.
How to Confirm Configuration Is Complete
- Run the MongoDB version query command, confirm the current version is in the 6.0 or 7.0 series to match configuration requirements.
- Log in to the database management interface, check the match between the
DB_MAX_LINKconfiguration value and current concurrent access volume. Ensure connection counts are not exhausted. - Submit a requirement change ticket search request, verify that the number of returned results matches expectations. Confirm index configurations are active.
- View the Redis cache monitoring dashboard, confirm that frequently accessed PRD document metadata has been successfully cached, with no connection errors.
The values provided are common starting points, and should be evaluated 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.