What the data for this category looks like
The data for this category mainly comes from engine Profiler performance sampling, crash platform log collection, real-device test frame rate collection, and resource occupancy monitoring tools. Daily produced documents include single-version performance test reports, full-model adaptation lists, iterative optimization records, and crash analysis summary tables. The data update frequency is usually daily or before each version release. Data fields include frame rate values, resource occupancy peaks, number of covered model adaptation cases, number of crash log entries, etc. There is no unified standardized format, and sorting must be done according to project requirements.
What constraints these characteristics impose on the "scheduled tasks and automation" workflow
Data sources are scattered and formats are inconsistent. Scheduled tasks must adapt to multi-source data pull logic, and fixed template parsing cannot be used. There are two update frequency rhythms: daily and version-level. Scheduled tasks must support switching between the two trigger cycles to avoid data omission or redundant execution caused by adapting to a single cycle. Documents have no standardized structure. Automated summary requires configuring field mapping rules to prevent summary failures or missing fields due to document format changes. Data from real-device tests and crash platforms has delays. Scheduled tasks must reserve data synchronization buffer time to prevent pulling incomplete, uncompleted data. Data related to performance optimization has high timeliness requirements. Scheduled task execution failures must trigger alerts to avoid delaying version releases or affecting subsequent optimization iterations.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Task Trigger Cycle | Calibrated based on actual testing (1 hour / daily / 1 day before version release) | Adapts to both daily and version-level data update rhythms |
| Data Pull Timeout Threshold | 600 seconds | Adapts to the delay characteristics of multi-source data pulls and avoids single-task blocking |
| Field Mapping Rules | Customized according to project document templates | Adapts to non-standardized performance optimization document formats |
| Failed Retry Count | 3 times | Addresses task failures caused by temporary network fluctuations or data synchronization delays |
| Alert Trigger Threshold | 2 consecutive task failures | Notifies relevant teams in a timely manner to handle exceptions |
| Summary Output Format | PDF / structured table | Adapts to the daily review habits of client engineers |
Three common mistakes
- Symptom: The model adaptation list field in the regularly generated summary report is empty. Cause: No field mapping rules are configured, or the mapping rules do not match the current document format, causing automated summary to fail to recognize target fields.
- Symptom: No alert notification is triggered after task execution. Cause: The alert trigger threshold is set too high, or the alert channel configuration is missing, preventing timely delivery of exception information.
- Symptom: Specified reply content is not saved to conversation history. Cause: Conversation history automatic storage configuration is not enabled, or scheduled tasks do not synchronously update history record storage logic, resulting in loss of interactive data during the optimization process.
How to confirm the configuration is complete
- Manually trigger a scheduled task, and verify whether records of successful data pulls exist in task logs.
- Review the summary output report to confirm that all configured fields have been correctly extracted and displayed.
- Simulate a task failure scenario to confirm whether the preset alert notification is triggered.
- Confirm that the currently running FastGPT version is v4.17.0 to ensure configuration items are compatible with platform functions.
- Adjust the task trigger cycle to verify whether the scheduled task automatically executes at the expected time.
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.