What Does the Data for This Category Look Like?
The data sources for this category are SIEM, EDR, NDR, and external threat intelligence feeds. Update cadence falls into two categories: real-time alert streams and daily summary documents. Daily output documents include alert handling tickets, duty logs, threat intelligence briefings, daily and weekly reports. Fields cover alert ID, handling status, judgment conclusions, dispatch targets, response duration, and more. Only standardized security operation data is recorded per business processes, with no additional custom statistical figures.
What Constraints Do These Characteristics Impose on Workflow Orchestration?
Real-time updated alert data requires workflows to support low-latency triggering. Long fixed polling intervals are not acceptable. Differentiated field structures across multiple document types require workflows to have flexible data source mapping capabilities to adapt to formats of different business documents. High-time-consuming links such as alert judgment and false positive elimination require workflows to include built-in standardized handling nodes to reduce repetitive operations. Cross-team handoff requirements for escalated dispatch require workflows to support role permission binding and operation trace recording. Severe error consequences require workflows to include built-in failure retry and exception notification mechanisms to avoid missed real attacks or response timeouts.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Timing | Triggered by real-time alert streams, interval no more than 60 seconds | Matches real-time alert update cadence of SIEM and NDR, avoids missed alert delays |
| Data Source Adaptation | Follow field mapping rules defined in variables | Adapts to field differences across multiple documents such as alert handling tickets and duty logs, unifies data input formats |
| Single Node Timeout Setting | 120 seconds | Covers typical time spent on alert judgment and intelligence query, avoids mid-process interruptions |
| Failure Retry Strategy | First 2 retries with 300-second interval, 3rd retry triggers manual intervention | Addresses temporary network fluctuations or temporary unavailability of intelligence feeds, reduces misjudgment probability |
| Workflow Handoff Permission Binding | Bind to corresponding team roles via nodeId | Differentiates node operation permissions for SOC analysts and duty supervisors, complies with security duty process specifications |
| Context Cache Retention Duration | 7 days | Matches statistical cycle of daily and weekly reports, facilitates cross-day judgment and traceability |
Three Common Misconfigurations
- Phenomenon: Canvas drag delay exceeds 5 seconds when the number of nodes exceeds 20. Cause: Lightweight rendering configuration for the workflow is not enabled, and nodes are not arranged in groups by function. This lag issue has been optimized in FastGPT v4.17.0 with updated node rendering logic.
- Phenomenon: The workflow outputs results normally on the run preview page, but returns no content on the chat page. Cause: The workflow's output node is not bound to the conversation context, or the conversation-triggered workflow switch is not enabled.
- Phenomenon: When the HTTP request node selects the form-data type, file parameters cannot be uploaded correctly. Cause: No file-type variable binding is defined in
variables, or the request header for file upload is not configured correctly.
How to Verify Proper Configuration
- Trigger a simulated alert data set, check if the workflow starts automatically and follows preset node handoffs.
- View the workflow log panel, confirm that the execution duration of each node matches the preset timeout settings.
- Simulate a node execution failure scenario, check if the preset retry mechanism and manual intervention notification are triggered.
- Switch accounts with different roles, verify that node operation permissions comply with configured role binding rules.
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.