What the data for this category looks like
Data for this category is maintained by SREs, technical leads, and quality teams. Four types of documents are produced regularly: RCA reports, incident tickets, review minutes, and rectification tracking sheets. Data sources include incident timelines, system logs, monitoring metrics, and code commit records. Updates occur after each major incident or once per month. Document fields must cover incident occurrence time, root cause classification, verification process, rectification items, and tracking status. All data must align with the business logic of incident reviews, with no additional fabricated statistical content.
What constraints these characteristics impose on forms and interactions
Data sources for this category are scattered, update rhythms are inconsistent, and document field logic is clear. These factors create multiple constraints for forms and interactions. Dispersed multi-source data requires external business systems to cooperate with form input nodes to implement field grouping by incident timeline, logs, monitoring metrics, and other categories, to avoid entry confusion. The urgent update requirement after a single major incident requires external business systems to provide preset templates and quick fill options to reduce filling time. Form input nodes are responsible for collecting user input information. Clear business field logic, such as root cause classification and rectification status, requires external business systems to provide interactive components with preset options to reduce format differences caused by free input. Form input nodes are responsible for collecting this type of input information. At the same time, the evidence collection link takes up a high proportion of time. External business systems can set convenient file upload entrances to lower operation thresholds. Form input nodes are responsible for collecting uploaded file information and passing it to subsequent nodes.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form Input Node formInput | Test example: Select 3 fields from incident management and root cause analysis fields as required inputs; actual fields are determined based on the task | This node collects user input; required fields must be checked for interaction status to avoid subsequent nodes failing to receive complete input |
User Selection Node userSelect | Test example: Set 2 business options, check corresponding branches one by one | This node handles user selection; querying and filtering records related to incident management and root cause analysis must be implemented by subsequent interfaces or external systems |
| Post-Submission Field Passing | Test example: Prepare 10 incident management and root cause analysis input samples, covering complete filling, missing required fields, and canceled operations | Compare input and node output to verify whether subsequent nodes receive corresponding fields; result thresholds are determined based on actual tasks |
| External Implementation Item: Incident Classification Drop-Down | Must be implemented separately by external systems; external business systems or subsequent nodes preset a fault root cause type library, including options such as system faults, code defects, and configuration errors | Match the root cause classification field of RCA reports to ensure unified data format |
| External Implementation Item: Model Selection Drop-Down | Must be implemented separately by external systems; external business systems or subsequent nodes provide a model option list; commonly used models are recommended as initial options | Adapt to the text generation requirements of root cause analysis, reducing the complexity of manual user input |
| External Implementation Item: Multi-Line Text Input Configuration | Must be implemented separately by external systems; set as a multi-line text box; external business systems or subsequent nodes configure character input length limits; recommended test value is 800–1200 characters | Match the content length of incident review minutes to accommodate detailed evidence descriptions |
Three common mistakes
- Symptom: The AI model drop-down list displays as empty, and no available models can be selected. Verification action: Check whether the external business system or subsequent node has configured the model data source, and confirm the binding relationship between the data source and the form input node.
- Symptom: Unauthorized referenced content is still returned after submitting the form. Verification action: Check whether the permission verification logic of the external business system or subsequent node is bound to the submission action of the form input node, and confirm that the verification rule configuration is correct.
- Symptom: After selecting a root cause classification, the associated fields are not automatically updated according to the rules. Verification action: Check whether the external business system or subsequent node has configured field linkage rules, and confirm the binding relationship between the linkage trigger condition and the form input node.
How to confirm the configuration is complete
- Open the configuration interface of the form input node, check whether the root cause type options provided by the external business system or subsequent node have been loaded, and confirm that the options match the fields of the business documents.
- Submit a test form, check whether the model selection drop-down loads the available model list provided by the external business system or subsequent node, and verify that the data source binding configuration is effective.
- Simulate the selection operation of the root cause type, confirm whether the associated fields are automatically updated according to the linkage rules configured by the external business system or subsequent node, and verify that the linkage logic is configured correctly.
- Fill in the required fields and submit, check whether the verification prompt configured by the external business system or subsequent node pops up, and verify that the data verification logic is working properly.
The values provided here 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.