What the data for this category looks like
Data for this category primarily comes from cloud database consoles, slow logs, monitoring metrics, and ticket systems. Some data must be pulled using cloud vendor open APIs. Daily generated documents include instance change orders, backup and recovery records, performance diagnostic reports, and parameter adjustment records. Data fields cover instance unique identifiers, change operation types, backup file sizes, slow SQL execution durations, monitoring metric thresholds, and additional relevant fields. Units include bytes, seconds, entries, and others. Data updates occur either via daily scheduled generation or immediate updates following instance changes. There is no unified fixed update cycle. Updates are triggered synchronously with operations and maintenance actions.
What constraints these characteristics impose on scheduled tasks and automation
Multiple scattered data sources require scheduled tasks to interface with open API endpoints from different cloud vendors. Adaptations must be made for each endpoint’s call frequency limits and authentication rules. Data updates have no unified fixed cycle. Task scheduling must support both daily scheduled full data pulls and incremental pulls triggered immediately after operations and maintenance changes. Document field types and units vary across sources. The summary process requires unified field mapping rules to avoid unit conversion errors or missing fields. In multi-tenant operations and maintenance scenarios, tasks must strictly isolate database data across different tenants to prevent cross-tenant data leaks.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Task Trigger Mode | Hybrid trigger: Full pull at 00:00 daily + incremental pull 10 minutes after instance change completion | Adapts to data update frequencies, balances full summary and real-time synchronization requirements |
| Pull Timeout | 300 seconds | Covers normal response durations for most cloud database APIs, avoids long-term blocking of task queues |
| Field Mapping Rules | Standard field mapping by instance ID, change time, operation type, and metric value | Unifies field formats across different data sources, ensures consistent summarized data |
| Alert Trigger Threshold | Trigger alert after 1 task execution failure | Responds to anomalies promptly, avoids delays in operations and maintenance data summary impacting decision-making |
| Retry Count | 2 retries, 60-second interval | Addresses temporary network fluctuations or temporary API unavailability, reduces false task failures |
This configuration description applies to FastGPT v4.17.0.
Three common configuration errors
- Scheduled tasks fail to run, and task logs display "Trigger condition not matched". The root cause is that hybrid triggering is configured, but the trigger callback after instance changes is not set correctly. Only daily scheduled pulls are used, resulting in temporary change data not being included in the summary.
- Pulled slow log data fields are empty. The root cause is that access permissions for the slow log API are not configured, preventing retrieval of log information from the corresponding data source.
- Backup size units in summary reports are inconsistent, with mixed MB and GB values. The root cause is that unified field mapping rules are not enabled, and units from different data sources are not standardized for conversion.
How to verify correct configuration
- Manually trigger an incremental pull task, and check if the task execution log successfully pulls the latest instance change order data.
- Randomly select a piece of raw data from the cloud database console, and verify that the summarized data fields and units comply with the preset mapping rules.
- Simulate a task execution failure scenario, and confirm that the preset alert notification is triggered.
- Check the multi-tenant isolation configuration, and confirm that tasks from different tenants cannot access each other’s database data.
The values given 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.