What data for this category looks like
Data for this category is generated around post-incident root cause analysis and prevention. Sources include incident timelines, operational logs, monitoring metrics, and code commit records. Daily produced documents include RCA reports, incident tickets, review minutes, and rectification tracking sheets. Fields cover incident occurrence time, impact scope, associated log snippets, root cause hypotheses, verification results, rectification items, and tracking status. Data is updated for each major incident or once per month. The content size of a single document varies based on incident complexity.
What constraints do these characteristics impose on workflow orchestration
Data sources for this category are scattered and cross-system. Workflow orchestration must support connecting multiple nodes to pull data from different sources such as incident timelines, logs, and monitoring metrics. Document fields are closely linked, and update frequency varies by incident scenario. Use variables to bind field mapping relationships to avoid data misalignment. The uncertainty of incident root cause analysis requires workflow orchestration to support branch decision nodes. These nodes adapt to verification paths for different root cause hypotheses. The rectification tracking progress synchronization logic requires workflow orchestration to include status synchronization nodes. This ensures document updates match actual rectification progress. Incorrect configuration will directly lead to root cause analysis deviations, causing repeated incidents or ineffective rectification.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Bind via field mapping for RCA reports and incident tickets | Document fields for this category are closely linked. Variable binding ensures accurate data transfer |
nodeId | Assign a unique identifier to each data source pull node | Prevents node call conflicts in multi-data-source pull scenarios |
| Single data pull limit | Top 20 entries | Adapts to the content size of single documents in this category, avoids node overload |
| Branch trigger rule | Trigger based on root cause hypothesis type | Adapts to the uncertainty of incident root cause analysis, supports different verification paths |
| Status synchronization interval | Calibrated via actual testing | Matches the update frequency of rectification tracking, ensures alignment between documents and actual progress |
| Node timeout threshold | 600 seconds | Adapts to the time required for cross-system log and monitoring data pulls |
Three common misconfigurations
- Symptom: Associated log snippets extracted after workflow runs are empty. Cause: No field mapping for log data sources bound via
variables, causing nodes to fail to pull corresponding data. - Symptom: Workflow debug returns an error indicating node ID conflict. Cause: No unique
nodeIdassigned to different data source nodes, leading to call confusion. This issue occurs occasionally in FastGPT v4.17.0. - Symptom: Workflow does not execute branch judgments as expected after triggering. Cause: Branch trigger rules are configured with fixed logic, not matched to root cause hypothesis types, and cannot adapt to verification needs for different incident scenarios.
How to confirm configurations are properly set
- Check that fields bound via
variablescorrespond one-to-one with fields in RCA reports and incident tickets, confirm the mapping relationship is correct. - Verify that
nodeIdfor each data source node is unique to avoid call conflicts. - Confirm that branch trigger rules match the classification logic of root cause hypotheses, ensuring adaptability to different incident scenarios.
- Test the node timeout threshold and status synchronization interval configurations, ensuring they meet actual time requirements for cross-system data pulls.
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.