What Data Looks Like for This Category
Data for SOC duty scenarios primarily comes from SIEM, EDR, NDR, and threat intelligence sources. Update cadence falls into two categories: real-time alert streams and daily summary reports. Daily generated documents include alert disposal tickets, duty logs, threat intelligence bulletins, and daily and weekly reports. Alert disposal tickets contain these fields: alert ID, source IP, disposal status, handler, timestamp. Duty logs include these fields: duty shift, abnormal events, dispatch information. Threat intelligence bulletins include these fields: threat level, IOC value, bulletin time.
Constraints on Database and Operations Workflows
Multiple heterogeneous data sources require databases to support both unstructured real-time writes and structured complex queries. Compatible configuration for multiple database types is therefore needed. Real-time alert streams generate high-concurrency write pressure. Appropriate connection pool and concurrency parameter configuration is required to avoid connection exhaustion or write timeouts. Batch data processing for daily summary reports needs separate batch execution configurations. These configurations prevent the occupation of real-time alert processing resources. Differences in fields across documents require databases to support flexible schema adaptation. This avoids write failures caused by field changes. Data reliability directly links to alert disposal efficiency. Data backup and verification mechanisms must be configured to prevent missed real attack alerts or false alert accumulation.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://soc_admin:secure_pass@db-host:27017/soc_db?authSource=admin&retryWrites=true | Adapts to unstructured storage for alert disposal tickets and threat intelligence bulletins, supports real-time high-concurrency writes |
PG_URL | postgresql://soc_ops:secure_pass@pg-host:5432/soc_operate?sslmode=require | Stores structured data such as duty logs and dispatch information, supports complex conditional queries |
DB_MAX_LINK | 20–30 connections | Addresses concurrent write demands for real-time alerts, avoids database connection exhaustion |
REDIS_URL | redis://:redis_pass@redis-host:6379/0 | Caches threat intelligence IOC data for high-frequency queries, reduces query load on primary databases |
Three Common Misconfigurations
- Symptom: MongoDB connection errors indicating version compatibility issues, or high-risk vulnerability alerts triggered by security scans. Cause: Official recommended secure MongoDB version is not used, and outdated images with known vulnerabilities are deployed directly.
- Symptom: Batch alert disposal tasks run slowly, with severe queue backlogs. Cause: Concurrent execution configuration is not enabled, and single-threaded processing is used by default, which cannot meet batch processing demands for real-time alerts.
- Symptom: Empty results are returned when querying knowledge base content, or database data for specified tenants cannot be read. Cause: Incompatible database type is incorrectly configured, or correct tenant and table name paths are not specified, resulting in failure to locate and read data normally.
How to Verify Correct Configuration
- Log in to the FastGPT v4.17.0 backend database configuration page, verify the connection status of
MONGODB_URI,PG_URL, andREDIS_URL, and confirm that normal connection is displayed. - Submit a simulated alert data entry, check whether corresponding records are generated in the target database to verify that real-time write function operates correctly.
- Run a batch disposal test task, check the task execution logs, and confirm that the number of concurrent execution threads meets the configured requirements.
- Attempt to export trained knowledge base content, confirm that corresponding data can be read according to the specified tenant and table name paths.
The configuration values provided here 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.