What this category of data looks like
This category of data primarily comes from CMDB systems, cloud resource inventories, automated discovery tools, and procurement ledgers. Core daily deliverables include configuration item lists, service component relationship topologies, change records, and asset inventory sheets. Data is updated daily or weekly. Core fields include configuration item unique identifiers, affiliated business services, dependency relationships, last update time, and more. The data structure must match the hierarchy and dependency links of operation and maintenance assets to ensure consistency and traceability of asset information.
What constraints do these characteristics impose on the "workflow orchestration" link
The scattered nature of data sources requires workflows to be configured with multi-source data pull nodes that connect to different systems such as CMDB and cloud resource inventories, avoiding errors from manual imports. Differences in update frequencies require workflows to support scheduled triggers on a daily or weekly basis, adapting to the update rhythms of different assets. Unlike IT asset inventory, this category requires focused verification of service component dependency relationships, so workflows must include a relationship checking step to ensure the accuracy of topology data. The most time-consuming collection and checking steps must be automated through workflow orchestration, reducing manual intervention time costs and improving the efficiency of document drafting.
How to set configurations
The following configurations are based on the workflow functionality of FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Global Variables | Configure asset ID prefixes and business service classifications in variables | Adapt to the unified format of CMDB data and reduce repeated entry of configuration item information |
| Node ID Binding | Bind nodeId to multi-source data pull nodes and relationship verification nodes | Ensure the execution order of each workflow step and the correct data flow path |
| Trigger Timing | 2 AM daily, 1 AM every Monday | Adapt to the daily/weekly data update rhythm and avoid peak business hours |
| Result Filter Threshold | Keep the top 5 matching configuration item data | Focus on core asset information and avoid redundant data interfering with document drafting |
| Node Timeout Setting | 600 seconds | Adapt to the average response time of multi-source data pulls and avoid workflow freezes |
| Intermediate Node Output Rules | Block the output of intermediate AI conversation nodes | Prevent intermediate draft content from being mixed into the final requirements and design documents |
Three Common Errors
- The final workflow result includes draft content from intermediate AI conversations: The phenomenon is that the document output after execution includes unpolished content generated by intermediate nodes. The cause is that the output blocking rule for intermediate nodes is not configured, causing intermediate results to be automatically included in the final workflow chain.
- Global variables do not take effect in the workflow: The phenomenon is that configuration item fields are empty or their values do not match the CMDB format. The cause is that preset parameters are not correctly bound in
variables, or the configured global variables are not referenced in the corresponding nodes. - Multi-source data pull nodes return empty results: The phenomenon is that the execution status of the CMDB or cloud resource inventory node is failed. The cause is that correct data source connection parameters are not configured, or the trigger timing does not match the data update cycle.
How to Confirm Configurations Are Set Properly
- Trigger a test workflow, view the execution logs of each node, and confirm that the configuration item data returned by the multi-source data pull nodes matches the actual content in CMDB and cloud resource inventories.
- Open the workflow's variable configuration panel, check whether the preset asset classification, ID prefix and other parameters in
variablesmatch the format of actual operation and maintenance documents. - Simulate the execution of an intermediate AI conversation node, verify that the final output result does not include draft content from intermediate steps, and confirm that the output blocking rule is active.
- Adjust the trigger timing to a test window, manually trigger the schedule, check whether the workflow starts automatically at the set time, and confirm that the schedule configuration is correct.
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.