What this category of data looks like
This category of data primarily comes from package managers, code repositories, vulnerability databases, and license databases. Daily generated documents include SBOM lists, dependency risk reports, license lists, and repair work orders. Core fields include third-party component names, version numbers, associated vulnerability IDs, license types, risk levels, and impact scopes. Data is updated daily or synchronized upon each version release. It covers all currently deployed open-source dependency assets, and applies to the local deployment scenario of FastGPT v4.17.0.
What constraints these characteristics impose on database and operations workflows
Multi-source data access requires the database to support batch writes in multiple structured formats. Frequent daily or version-level updates create continuous write pressure. Sufficient connection and storage resources must be reserved. Multi-field document structures require targeted index creation to avoid full table scans that slow query speeds. Different types of risk reports and work order data must be stored in separate tables by business scenario to reduce single-table data volume. Data anomalies directly affect dependency governance results. Database high availability and rapid fault recovery capabilities must be ensured.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Intranet-accessible MongoDB connection address, such as mongodb://user:pass@host:27017/fastgpt | Adapts to offline deployment scenarios, avoids external network dependencies |
PG_URL | Intranet-accessible PostgreSQL connection address | Used to store license list and repair work order data |
DB_MAX_LINK | 64–128 connections | Matches the concurrent processing capability of servers with 64 or more CPU cores, prevents connection exhaustion |
REDIS_URL | Intranet-accessible Redis connection address | Used to cache dependency risk data from frequent queries |
| Database backup cycle | Daily at 00:00 | Aligns with daily data update rhythm, ensures recovery of the most recent complete data after a fault |
| Batch write threshold | 50–100 items per request | Balances write efficiency and server IO load, adapts to frequent SBOM data imports |
Three common misconfigurations
getaddrinfo EAI_AGAIN mongoerror occurs after restarting: The service cannot resolve MongoDB addresses during startup, and cannot establish a database connection. The root cause is that the domain name configured inMONGODB_URIis not correctly added to the local hosts file, or local DNS cache has not been updated promptly.- If dependency-data writes freeze, disk usage remains at 100%, or SBOM imports time out, distinguish capacity pressure, I/O waits, database locks, queued tasks, and upstream response delays. Inspect monitoring and task logs before attributing the problem to missing cleanup rules. Size storage from data volume, indexes, and retention needs; do not assert an unverified universal minimum.
- Excessively high delay in dependency risk report queries: Query results take more than 30 seconds to return, or some fields are empty. The root cause is that no joint index is created based on component name and version number, causing the database to perform a full table scan and slow down query speed.
How to confirm correct configuration
- Run a database connection test command to verify that the addresses configured in
MONGODB_URIandREDIS_URLcan establish normal connections, with no timeouts or resolution errors. - Check disk capacity and I/O monitoring. A 20% free-space alert is only an operational example and should be calibrated to actual growth. If the deployment defines a cleanup task, first verify backups, cleanup scope, and recovery in an isolated environment.
- Initiate a dependency data import test using the 50–100 items per request batch write threshold, confirm that write delay meets expectations, and there is no IO blocking.
- Initiate a risk report query to confirm that returned results are complete, and delay falls within an acceptable range.
The values provided here are common starting points, and should be evaluated against local deployment 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.