What data for this category looks like
Data sources for this category include pressure testing platforms, APM monitoring, database slow logs, and production traffic baselines. Regularly produced documents include pressure testing plans, capacity evaluation reports, pressure testing data records, and optimization suggestion sheets. Document fields include throughput (unit: requests/second), average latency (unit: milliseconds), CPU/memory usage (unit: %), concurrent connection count (unit: count), and others. Data is updated once per month or when major software versions are released. Documents must be linked to pressure testing and evaluation results for the corresponding version.
What constraints these characteristics impose on workflow orchestration
Multiple data sources require workflows to configure multiple nodes to connect to different sources, to avoid evaluation bias from a single data source. Differences in field units across documents require unified field mapping rules during orchestration, to ensure consistent data formats. Monthly or major version update cycles require workflows to bind version identifiers, to facilitate historical configuration tracing. The most time-consuming links—pressure testing model design, bottleneck identification, and capacity conclusion review—must be split into independent workflow nodes to support segmented debugging and review. A failure alert node must also be configured, to prevent online resource issues caused by evaluation errors.
Configuration guidelines
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
| Variable selection | Bind 3 types of data sources: pressure testing platforms, APM monitoring, database slow logs | Cover all dimensions of performance evaluation data sources |
| Node ID | Assign in order of workflow nodes, such as node1, node2 | Facilitate debugging and tracing of workflow nodes |
| Concurrency threshold | Set to 30-50 concurrent connections for 4c16g nodes | Match the carrying capacity of single-node hardware resources |
| Pressure testing duration | 600-1200 seconds | Ensure stable pressure testing data samples are collected |
| Number of failure retries | 2 | Balance data integrity and execution efficiency |
| Platform version | Adapt to FastGPT v4.17.0 | Ensure configuration items are compatible with platform functions |
Three common configuration mistakes
- API access keys are not correctly linked to workflow nodes. Symptoms: API calls return a 401 status code. Cause: Correct node access permissions are not bound.
- Single-node concurrency threshold is set above 50. Symptoms: Node processes terminate abnormally, return a 503 status code. Cause: Concurrency upper limit is not calibrated according to node hardware resources.
- Variable mapping is not configured in the JSON input box. Symptoms: Pressure testing parameter fields are empty. Cause: The variable selection switch is not enabled.
How to confirm correct configuration
- Verify that the variable selection configuration covers all required data source types, with no omissions.
- Run a test workflow, confirm that the concurrency count does not exceed the set threshold, and no abnormal processes or errors occur.
- Submit JSON-formatted pressure testing parameters, confirm that variables are properly mapped to the input box, and no fields are empty.
- View workflow logs, confirm that data from all data sources is pulled normally, with no connection or parsing errors.
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.