What this type of data looks like
Core data for ticket acceptance and issue classification comes from ticketing systems, chat logs, product logs, and customer contract SLAs, with an update frequency of daily or real-time. Daily produced documents include customer tickets, issue classification tables, processing records, and service reports. Fields include unique ticket identifiers, customer associated information, issue classification tags, classification levels, response time limit requirements, handlers, and statuses. The data covers the entire process from customer feedback submission to issue closure. Data from different sources has varying formats, so a unified input structure must be adapted during workflow orchestration.
What constraints these characteristics impose on the workflow orchestration link
Multi-source heterogeneous data input requires workflows to support multi-format variable parsing and adaptation, to avoid node execution failures caused by inconsistent data formats. Real-time or high-frequency updated ticket data requires workflow nodes to have reasonable concurrent carrying capacity, to prevent resource exhaustion in high-concurrency scenarios. Core time-consuming links (issue reproduction, impact scope judgment) require workflows to embed verification nodes to pre-verify key information, reducing invalid transfers. The error consequences of SLA violations require workflows to be configured with timeout alerts and abnormal transfer branches, ensuring that tickets not processed as required trigger alerts or automatic escalation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind ticket ID, issue classification fields, customer SLA thresholds | Adapt field extraction and transfer for multi-source data, ensuring each ticket node can obtain exclusive business parameters |
nodeId | Bind corresponding processing nodes based on issue classification results | Match the responsibility assignment logic after issue classification, enabling automatic ticket transfer |
| Single-node concurrency limit | 50-80 concurrency/node | Adapt to general server hardware carrying capacity, avoiding service exceptions caused by resource exhaustion |
| Timeout threshold | 600 seconds | Match the conventional response time limit requirements of customer contract SLAs, ensuring overdue tickets trigger alerts |
| Input verification rules | Verify that issue classification fields are not empty and ticket ID format is valid | Pre-filter invalid tickets, reducing invalid node execution |
Three common mistakes
- Exceeding the set single-node concurrency limit causes process unresponsiveness and returns a 503 status code. This occurs because the concurrency limit parameter is not adjusted based on server hardware configuration, leading to resource exhaustion.
- Returning 400 or 404 status codes when accessing the workflow via API, preventing normal process triggering. This occurs because the API call-required ticket interface parameters are not correctly configured in
variables, leading to missing or mismatched parameters. - Unable to select preset variables in the JSON input box, with an empty variable option list. This occurs because the workflow's variable mapping switch is not enabled, causing the input box to fail to associate with defined business variables.
How to confirm the configuration is complete
- Check the
variablesconfiguration item of the workflow in FastGPT v4.17.0, confirm that core business parameters such as ticket ID and issue classification fields have been bound. - Verify that the
nodeIdconfiguration corresponds one-to-one with the processing nodes after issue classification, ensuring tickets can be automatically transferred based on classification results. - Test the running status of single-node concurrency within the 50-80 range, confirming no resource exhaustion or response timeout issues.
- Call the API interface of the test ticket, check that the return status code is 200, and that the workflow can be triggered and transferred normally.
The values listed above 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.