What the Data for This Category Looks Like
This category's data primarily comes from SIEM, EDR, NDR, and external threat intelligence sources. Update cadence falls into two categories: real-time alert pushes and daily intelligence synchronization. Daily produced documents include alert disposal tickets, duty logs, threat intelligence reports, and daily/weekly reports. Data fields cover alert unique identifier, source IP address, threat type, judgment result, disposal status, dispatch time, and other fields. There are no custom aggregate statistical fields. The size of a single record is small, but the daily data volume fluctuates with alert trigger frequency.
How These Characteristics Create Constraints for Database and Operations Workflows
Real-time alerts with high-frequency writes require database connection pools to support high-concurrency short connection reuse, to avoid connection exhaustion. Batch writes for daily intelligence synchronization need batch submission thresholds configured, to prevent single-write timeouts. Access to multiple heterogeneous data sources requires databases to support flexible field expansion, without frequent table structure modifications to adapt to different alert and intelligence data formats. Full lifecycle retention of documents such as alert disposal tickets requires data archiving policies configured, to distinguish between hot and cold data storage while ensuring fast retrieval of historical data. Low-latency requirements for real-time judgment require database read-write separation nodes configured, to avoid main library read-write pressure overload affecting alert response speed.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://soc-admin:secure123@mongo-host:27017/soc_db?authSource=admin | Adapts to Docker-deployed MongoDB instances, supports account password and authentication source configuration, compatible with FastGPT v4.17.0 database connection logic |
PG_URL | postgresql://soc-user:pass456@pg-host:5432/soc_ops?sslmode=require | Ensures encrypted transmission of database connections, meets data compliance storage requirements for security scenarios |
DB_MAX_LINK | 60–100 connections | Matches real-time alert concurrent write requirements in SOC duty scenarios, avoids alert loss caused by connection pool exhaustion |
REDIS_URL | redis://:redis-pass@redis-host:6379/1 | Caches frequently queried alert judgment rules and duty logs, reduces read-write pressure on the main database |
| Batch Write Threshold | 150–250 entries per call | Adapts to batch write scenarios for daily threat intelligence synchronization, balances single write efficiency and timeout risk |
Three Common Misconfigurations
- Phenomenon: Unable to log in to the platform after performing a version upgrade, returns
500 Internal Server Error. Cause: Accidentally adjusted the authentication source or connection address parameter ofMONGODB_URIwhen modifying the MongoDB configuration file, resulting in failed database connection verification. - Phenomenon: Write timeout error occurs when batch importing daily threat intelligence. Cause: No reasonable batch write threshold configured, single write data volume exceeds the database's carrying capacity.
- Phenomenon: Large number of duplicate push records for real-time alerts. Cause: No Redis cache alert deduplication rule configured, causing duplicate alert requests to be written to the database repeatedly, resulting in data redundancy.
How to Verify Successful Configuration
- Execute the
mongo --uri $MONGODB_URIcommand to verify whether the MongoDB database connection is normal, adjust configuration parameters based on the connection result. - Submit test alert data, check the database write log to confirm whether the data is stored in the corresponding database tables in the expected format.
- Check the Redis service connection status to confirm whether the cache service responds normally, verify whether the alert deduplication rule takes effect.
- Simulate daily batch intelligence import operations, check whether the write time meets business expectations, adjust the batch write threshold as needed.
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.