What this type of data looks like
Test cases and defect analysis data for trusted innovation replacement adaptation comes from existing system inventories, domestic hardware and software directories, test environment configurations, and publicly available vendor materials. Update frequency is per project or quarterly. Core documents include adaptation lists, compatibility test reports, migration plans, and issue ledgers. Data fields cover hardware and software models, adaptation status, defect severity, test environment parameters, migration risk level, and more. Field structures must be adjusted per individual project requirements, with no unified fixed format.
What constraints these characteristics impose on the workflow orchestration link
Dispersed data sources with no unified format require workflows to support connection to multiple types of data source nodes, and automatically adapt to document inputs of different formats. Update frequency adjusted per project cycle requires workflows to support versioned configuration, enabling reuse or modification across different projects. Core documents include multiple types of business files, requiring that test data and reports of different types can be transferred between workflow nodes. Additionally, the most time-consuming step in this category is inventorying existing systems and conducting compatibility testing. This requires workflows to automate repetitive test steps, reduce manual operation errors, and configure failure retry and alert nodes to avoid migration delays caused by test interruptions.
Configuration guidelines
The following configurations are adapted for FastGPT v4.17.0:
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Data Source Node Timeout | 300-600 seconds | Test data mostly comes from dispersed hardware and software directories, so sufficient time is needed for pulling and verification |
variables | Bind core fields of adaptation lists and defect ledgers | Uniformly transfer full data for test cases and defect analysis, prevent data loss during transfer between nodes |
nodeId | Assign node IDs in the order of compatibility test links | Ensure workflow nodes execute in the order of "inventory existing systems → compatibility testing → defect summary" |
| Log Output Path | Project-specific log directory | Facilitate troubleshooting of console logs for code execution modules, prevent log loss |
| Failure Retry Count | 2-3 times | Address occasional connection or verification failures in test environments, reduce manual intervention |
| Single Test Data Volume | First 1000 entries | Adapt to the initial data scale of existing system inventory, avoid timeouts caused by excessive single-load data |
Three common mistakes
- Symptom: Workflow fails to connect to MSSQL database with error
Failed to connect to jyfkk:1433 - 38BBDDC3AF7F0000. Cause: Correct database connection parameters are not configured invariables, causing the node to fail to recognize the target address and port. - Symptom: No compatibility test report is generated after workflow execution. Cause:
nodeIdis not configured in the order of test links, leading to broken node execution logic, and subsequent summary links cannot obtain pre-test data. - Symptom: Console logs for code execution modules cannot be viewed in the console. Cause: No log output path is configured, logs are not directed to the specified directory, and are only cached locally temporarily before being cleared.
How to confirm proper configuration
- Verify that the adaptation list and defect ledger fields bound in
variablesmatch the core fields in the project documentation. - Confirm that the
nodeIdassignment order follows the compatibility test process of "inventory existing systems → compatibility testing → defect summary". - Trigger a test link, and check whether corresponding output files are generated in the project-specific log directory.
- Simulate a database connection request, confirm that workflow nodes can normally pull data from the test environment.
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.